@article {clark2023asr, title = {Defining Allowable Stimulus Ranges for Position and Force Controlled Cutaneous Cues}, journal = {IEEE Transactions on Haptics}, volume = {16}, number = {3}, year = {2023}, month = {July-September}, pages = {353-364}, doi = {10.1109/TOH.2023.3286306}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/IEEE_ToH_2023_Clark_AllowableStimulusRangeSMALL.pdf}, author = {Clark, Janelle P and O{\textquoteright}Malley, Marcia K} } @article {JUMET2023100059, title = {Fluidically programmed wearable haptic textiles}, journal = {Device}, year = {2023}, pages = {100059}, abstract = {
Summary Haptic feedback offers a useful mode of communication in visually or auditorily noisy environments. The adoption of haptic devices in our everyday lives, however, remains limited, motivating research on haptic wearables constructed from materials that enable comfortable and lightweight form factors. Textiles, a material class fitting these needs and already ubiquitous in clothing, have begun to be used in haptics, but reliance on arrays of electromechanical controllers detracts from the benefits that textiles offer. Here, we mitigate the requirement for bulky hardware by developing a class of wearable haptic textiles capable of delivering high-resolution information on the basis of embedded fluidic programming. The designs of these haptic textiles enable tailorable amplitudinal, spatial, and temporal control. Combining these capabilities, we demonstrate wearables that deliver spatiotemporal cues in four directions with an average user accuracy of 87\%. Subsequent demonstrations of washability, repairability, and utility for navigational tasks exemplify the capabilities of our approach.
}, keywords = {analog control, fluidic control, haptic sleeve, human-machine interaction, human-robot interaction, Navigation, point force, smart textiles, spatiotemporal haptics, tactile cues}, issn = {2666-9986}, doi = {https://doi.org/10.1016/j.device.2023.100059}, url = {https://www.sciencedirect.com/science/article/pii/S2666998623000832}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/DeviceJumet2023.pdf}, author = {Barclay Jumet and Zane A. Zook and Anas Yousaf and Anoop Rajappan and Doris Xu and Te Faye Yap and Nathaniel Fino and Zhen Liu and Marcia K. O{\textquoteright}Malley and Daniel J. Preston} } @article {dunkelberger2023, title = {Hybrid FES-exoskeleton control: Using MPC to distribute actuation for elbow and wrist movements}, journal = {Frontiers in Neurorobotics}, volume = {17}, year = {2023}, pages = {1127783}, doi = {10.3389/fnbot.2023.1127783}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Frontiers_2023_Dunkelberger_hybridFESexo.pdf}, author = {Dunkelberger, Nathan and Berning, Jeffrey and Schearer, Eric M and O{\textquoteright}Malley, Marcia K} } @article {fino2023tactor, title = {Mechanofluidic Instability-Driven Wearable Textile Vibrotactor}, journal = {IEEE Transactions on Haptics}, year = {2023}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/IEEE_ToH_2023_Fino_wearabletactor.pdf}, author = {Fino, Nathaniel and Jumet, Barclay and Zook, Zane A and Preston, Daniel J and O{\textquoteright}Malley, Marcia K} } @article {pezent2023AIS, title = {Multisensory Pseudo-Haptics for Rendering Manual Interactions with Virtual Objects}, journal = {Advanced Intelligent Systems}, volume = {n/a}, number = {n/a}, year = {2023}, pages = {2200303}, abstract = {Recent advances in extended reality (XR) technologies make seeing and hearing virtual objects commonplace, yet strategies for synthesizing haptic interactions with virtual objects continue to be limited. Two design principles govern the rendering of believable and intuitive haptic feedback: movement through open space must feel {\textquotedblleft}free{\textquotedblright} while contact with virtual objects must feel stiff. Herein, a novel multisensory approach that conveys proprioception and effort through illusory visual feedback and refers to the wrist, via a bracelet interface, discrete and continuous interaction forces that would otherwise occur at the hands and fingertips, is presented. Results demonstrate that users reliably discriminate the stiffness of virtual buttons when provided with multisensory pseudohaptic feedback, comprising tactile pseudohaptic feedback (discrete vibrotactile feedback and continuous squeeze cues in a bracelet interface) and visual pseudohaptic illusions of touch interactions. Compared to the use of tactile or visual pseudohaptic feedback alone, multisensory pseudohaptic feedback expands the range of physical stiffnesses that are intuitively associated with the rendered virtual interactions and reduces individual differences in physical-to-virtual stiffness mappings. This multisensory approach, which leaves users{\textquoteright} hands unencumbered, provides a flexible framework for synthesizing a wide array of touch-enabled interactions in XR, with great potential for enhancing user experiences.
}, keywords = {augmented reality, bracelet, haptic interaction, haptics, Virtual reality, wearables}, doi = {https://doi.org/10.1002/aisy.202200303}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/aisy.202200303}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Advanced\%20Intelligent\%20Systems\%20-\%202023\%20-\%20Pezent\%20-\%20Multisensory\%20Pseudo\%E2\%80\%90Haptics\%20for\%20Rendering\%20Manual\%20Interactions\%20with\%20Virtual.pdf}, author = {Pezent, Evan and Macklin, Alix and Yau, Jeffrey M. and Colonnese, Nicholas and O{\textquoteright}Malley, Marcia K.} } @article {macklin2023toh, title = {Representational Similarity Analysis for Tracking Neural Correlates of Haptic Learning on a Multimodal Device}, journal = {IEEE Transactions on Haptics}, volume = {16}, number = {3}, year = {2023}, month = {July-September}, pages = {424-435}, doi = {10.1109/TOH.2023.3303838}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Macklin\%20et\%20al.\%202023.pdf}, author = {Macklin, Alix S and Yau, Jeffrey M and Fischer-Baum, Simon and O{\textquoteright}Malley, Marcia K} } @proceedings {2054, title = {A Soft Approach to Convey Vibrotactile Feedback in Wearables Through Mechanical Hysteresis}, year = {2023}, publisher = {IEEE}, doi = {10.1109/RoboSoft55895.2023.10122072}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Fino_2023_Robosoft.pdf}, author = {Fino, Nathaniel and Zook, Zane A and Jumet, Barclay and Preston, Daniel J and O{\textquoteright}Malley, Marcia K} } @article {sciro_brown2023, title = {Touching reality: Bridging the user-researcher divide in upper-limb prosthetics}, journal = {Science Robotics}, volume = {8}, number = {83}, year = {2023}, pages = {eadk9421}, abstract = {Realistically improving upper-limb prostheses is only possible if we listen to users{\textquoteright} actual technological needs. Realistically improving upper-limb prostheses is only possible if we listen to users{\textquoteright} actual technological needs.
}, doi = {10.1126/scirobotics.adk9421}, url = {https://www.science.org/doi/abs/10.1126/scirobotics.adk9421}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/SciRoboticsBrown2023_prosthesis_users.pdf}, author = {J. D. Brown and E. Battaglia and S. Engdahl and G. Levay and A. C. Parks and E. Skinner and M. K. O{\textquoteright}Malley} } @article {9788113, title = {Design, Characterization, and Dynamic Simulation of the MAHI Open Exoskeleton Upper Limb Robot}, journal = {IEEE/ASME Transactions on Mechatronics}, volume = {27}, number = {4}, year = {2022}, month = {06/2022}, pages = {1829-1836}, doi = {10.1109/TMECH.2022.3175507}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Dunkelberger_TMECH_AIM.pdf}, author = {Dunkelberger, Nathan and Berning, Jeffrey and Dix, Kevin J. and Ramirez, Samuel A. and O{\textquoteright}Malley, Marcia K.} } @article {PezentTRO2022, title = {Design, Control, and Psychophysics of Tasbi: A Force-Controlled Multimodal Haptic Bracelet}, journal = {IEEE Transactions on Robotics}, volume = {38}, number = {5}, year = {2022}, pages = {2962-2978}, doi = {10.1109/TRO.2022.3164840}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/IEEE_TRO_2022_Pezent_Tasbi.pdf}, author = {Pezent, Evan and Agarwal, Priyanshu and Hartcher-O{\textquoteright}Brien, Jessica and Colonnese, Nicholas and O{\textquoteright}Malley, Marcia K.} } @proceedings {2023, title = {Effect of Focus Direction and Agency on Tactile Perceptibility}, year = {2022}, publisher = {Springer International Publishing}, address = {Cham}, abstract = {Prior research has shown that the direction of a user{\textquoteright}s focus affects the perception of tactile cues. Additionally, user agency over touch stimulation has been shown to affect tactile perception. With the development of more complicated haptic and multi-sensory devices, simple tactile cues are rarely used in isolation and the effect of focus direction and of user agency on the perception of a sequence of tactile cues is unknown. In this study, we investigate the effect of both of these variables, focus direction and agency, on the perception of a cue sequence. We found that the direction of user focus and user sense of agency over tactile stimulation both had a significant effect on the accurate perception of a cue sequence. These results are presented in consideration for developing better haptic devices that account for users{\textquoteright} focus on and control over these devices.
}, isbn = {978-3-031-06249-0}, url = {https://link.springer.com/chapter/10.1007/978-3-031-06249-0_14$\#$citeas}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/EuroHaptics_2022_Zook_Focus_Direction_And_Agency_Haptics.pdf}, author = {Zook, Zane A. and O{\textquoteright}Malley, Marcia K.}, editor = {Seifi, Hasti and Kappers, Astrid M. L. and Schneider, Oliver and Drewing, Knut and Pacchierotti, Claudio and Abbasimoshaei, Alireza and Huisman, Gijs and Kern, Thorsten A.} } @article {2006, title = {Effect of Tactile Masking on Multi-Sensory Haptic Perception}, journal = {IEEE Transactions on Haptics}, volume = {15}, number = {1}, year = {2022}, month = {03/2022}, pages = {212-221}, chapter = {212}, issn = {1939-1412}, doi = {10.1109/TOH.2021.3112509}, url = {https://ieeexplore.ieee.org/document/9540350/http://xplorestaging.ieee.org/ielx7/4543165/4543166/09540350.pdf?arnumber=9540350}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Zook_ToH_2022_tactile-masking.pdf}, author = {Zook, Zane and Fleck, Joshua and O{\textquoteright}Malley, Marcia K} } @article {legeza2022eval, title = {Evaluation of Robotic-Assisted Carotid Artery Stenting in a Virtual Model Using Motion-Based Performance Metrics}, journal = {Journal of Endovascular Therapy}, year = {2022}, pages = {15266028221125592}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Legaza_JET2022.pdf}, author = {Legeza, Peter T and Lettenberger, Ahalya B and Murali, Barathwaj and Johnson, Lianne R and Berczeli, Marton and Byrne, Michael D and Britz, Gavin and O{\textquoteright}Malley, Marcia K and Lumsden, Alan B} } @proceedings {2057, title = {Explorations of wrist haptic feedback for AR/VR interactions with Tasbi}, year = {2022}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Pezent_CHI_2022.pdf}, author = {Pezent, Evan and Gupta, Aakar and Duhaime, Hank and O{\textquoteright}Malley, Marcia and Israr, Ali and Samad, Majed and Robinson, Shea and Agarwal, Priyanshu and Benko, Hrvoje and Colonnese, Nick} } @article {2016, title = {Haptic feedback based on movement smoothness improves performance in a perceptual-motor task}, journal = {IEEE Transactions on Haptics}, volume = {15}, number = {2}, year = {2022}, month = {2022}, pages = {382-391}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/IEEE_ToH_2021_Sullivan_haptic-feedback-smoothness-MT5.pdf}, author = {Sullivan, Jennifer L and Pandey, Shivam and Byrne, Michael D and O{\textquoteright}Malley, Marcia K} } @proceedings {2038, title = {Measuring Torque Production with a Robotic Exoskeleton during Cervical Transcutaneous Spinal Stimulation}, year = {2022}, month = {07/2022}, publisher = {IEEE}, address = {Rotterdam, Netherlands}, doi = {10.1109/ICORR55369.2022.9896477}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/ICORR_2022_Mahan_TSS_with_MAHI_ExoII.pdf}, author = {Erin Mahan and Nathan Dunkelberger and Jeonghoon Oh and Madison Simmons and Blesson Varghese and Dimitry Sayenko and Marcia K O{\textquoteright}Malley} } @article {IJRRLosey2021, title = {Physical interaction as communication: Learning robot objectives online from human corrections}, journal = {The International Journal of Robotics Research}, volume = {41}, number = {1}, year = {2022}, month = {Jan 2022}, pages = {02783649211050958}, chapter = {20-44}, abstract = {When a robot performs a task next to a human, physical interaction is inevitable: the human might push, pull, twist, or guide the robot. The state of the art treats these interactions as disturbances that the robot should reject or avoid. At best, these robots respond safely while the human interacts; but after the human lets go, these robots simply return to their original behavior. We recognize that physical human{\textendash}robot interaction (pHRI) is often intentional: the human intervenes on purpose because the robot is not doing the task correctly. In this article, we argue that when pHRI is intentional it is also informative: the robot can leverage interactions to learn how it should complete the rest of its current task even after the person lets go. We formalize pHRI as a dynamical system, where the human has in mind an objective function they want the robot to optimize, but the robot does not get direct access to the parameters of this objective: they are internal to the human. Within our proposed framework human interactions become observations about the true objective. We introduce approximations to learn from and respond to pHRI in real-time. We recognize that not all human corrections are perfect: often users interact with the robot noisily, and so we improve the efficiency of robot learning from pHRI by reducing unintended learning. Finally, we conduct simulations and user studies on a robotic manipulator to compare our proposed approach with the state of the art. Our results indicate that learning from pHRI leads to better task performance and improved human satisfaction.
}, doi = {10.1177/02783649211050958}, url = {https://doi.org/10.1177/02783649211050958}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Losey_IJRR2021.pdf}, author = {Dylan P. Losey and Andrea Bajcsy and Marcia K. O{\textquoteright}Malley and Anca D. Dragan} } @inbook {2020, title = {A Textile-Based Approach to Wearable Haptic Devices}, booktitle = {2022 IEEE 5th International Conference on Soft Robotics (RoboSoft)}, year = {2022}, doi = {10.1109/RoboSoft54090.2022.9762149}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Jumet_RoboSoft2022.pdf}, author = {Jumet, Barclay and Zook, Zane A. and Xu, Doris and Fino, Nathaniel and Rajappan, Anoop and Schara, Mark W. and Berning, Jeffrey and Escobar, Nicolas and O{\textquoteright}Malley, Marcia K. and Preston, Daniel J.} } @proceedings {2012, title = {Comparing Manual and Robotic-Assisted Carotid Artery Stenting Using Motion-Based Performance Metrics}, year = {2021}, month = {2021}, pages = {1388-1391}, doi = {10.1109/EMBC46164.2021.9630895}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Lettenberger_EMBC_2021_motion-based-metrics-manual-robot.pdf}, author = {Lettenberger, Ahalya B. and Murali, Barathwaj and Legeza, Peter and Byrne, Michael D. and Lumsden, Alan B. and O{\textquoteright}Malley, Marcia K.} } @article {dupont2021decade, title = {A decade retrospective of medical robotics research from 2010 to 2020}, journal = {Science Robotics}, volume = {6}, number = {60}, year = {2021}, pages = {eabi8017}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/scirobotics2021abi8017.pdf}, author = {Dupont, Pierre E and Nelson, Bradley J and Goldfarb, Michael and Hannaford, Blake and Menciassi, Arianna and O{\textquoteright}Malley, Marcia K and Simaan, Nabil and Valdastri, Pietro and Yang, Guang-Zhong} } @article {yousaf2021design, title = {Design and Characterization of a Passive Instrumented Hand}, journal = {ASME Letters in Dynamic Systems and Control}, volume = {1}, number = {1}, year = {2021}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/ALDSC-19-1082-1_Two_Col.pdf}, author = {Yousaf, Saad N and Joshi, Victoria S and Britt, John E and Rose, Chad G and O{\textquoteright}Malley, Marcia K} } @article {9563066, title = {Effect of Robotic Exoskeleton Motion Constraints on Upper Limb Muscle Synergies: A Case Study}, journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering}, volume = {29}, year = {2021}, pages = {2086-2095}, doi = {10.1109/TNSRE.2021.3118591}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/McDonald_TNSRE2021.pdf}, author = {Mcdonald, Craig G. and Fregly, Benjamin J. and O{\textquoteright}Malley, Marcia K.} } @article {1994, title = {Effects of Interfering Cue Separation Distance and Amplitude on the Haptic Detection of Skin Stretch}, journal = {IEEE Transactions on Haptics}, volume = {14}, number = {2}, year = {2021}, month = {April-June 2021}, pages = {254-259}, abstract = {Multi-sensory haptic cues, which contain several types of tactile stimuli that are presented concurrently to the user, have been shown to be useful for conveying information-rich cues. One limitation of multi-sensory cues is that user perception of individual cue components can be hindered by more salient components of the composite cue. In this paper, we investigate how amplitude and distance between cues affect the perception of multi-sensory haptic cues. Specifically, participants{\textquoteright} absolute threshold perception of stretch cues was measured in the presence of interfering squeeze cues using a modular testbed. We evaluated ten conditions of varying interference amplitude and distance between cues. We found that interference cue amplitude and distance between cues both have a statistically significant effect on the absolute perception of stretch cues. As interference cue amplitude increases, and as distance between cues decreases, absolute perception of stretch cues worsens. These results inform design considerations for future wearable multi-sensory haptic devices, so that cue salience can be maximized and interference effects minimized.
}, issn = {1939-1412}, doi = {10.1109/TOH.454316510.1109/TOH.2021.3075387}, url = {https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4543165https://ieeexplore.ieee.org/document/9415164/http://xplorestaging.ieee.org/ielx7/4543165/4543166/09415164.pdf?arnumber=9415164}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Low_ToH2021.pdf}, author = {Low, Andrew Kin Wei and Zook, Zane and Fleck, Joshua and O{\textquoteright}Malley, Marcia K} } @proceedings {britt2021emg, title = {Electromyographic Classification to Control the SPAR Glove}, volume = {54}, number = {20}, year = {2021}, pages = {244{\textendash}250}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Britt_MECC_IFAC_2021.pdf}, author = {Britt, John E and O{\textquoteright}Malley, Marcia K and Rose, Chad G} } @proceedings {2013, title = {Enhancing Multi-Sensory Cue Salience and Perceptual Identification in a Wearable Haptic Device}, year = {2021}, doi = {10.1109/WHC49131.2021.9517130}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Enhancing_Multi-Sensory_Cue_Salience_and_Perceptual_Identification_in_a_Wearable_Haptic_Device.pdf}, author = {Alexander, Stephen A. and Garcia, Roderico and O{\textquoteright}Malley, Marcia K.} } @article {2002, title = {Evaluating the Effect of Stimulus Duration on Vibrotactile Cue Localizability with a Tactile Sleeve}, journal = {IEEE Transactions on Haptics}, volume = {14}, number = {2}, year = {2021}, month = {April-June 2021}, pages = {328-334}, doi = {10.1109/TOH.2021.3079727}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Macklin_ToH2021.pdf}, author = {Macklin, Alix S. and Yau, Jeff and O{\textquoteright}Malley, Marcia K} } @article {9141429, title = {A Multi-sensory Approach to Present Phonemes as Language through a Wearable Haptic Device}, journal = {IEEE Transactions on Haptics}, volume = {14}, number = {1}, year = {2021}, month = {Jan-Mar 2021}, pages = {188-199}, doi = {10.1109/TOH.2020.3009581}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/IEEE_ToH_2020_Dunkelberger_small.pdf}, author = {N. Dunkelberger and J. L. Sullivan and J. Bradley and I. Manickam and G. Dasarathy and R. G. Baraniuk and M. K. O{\textquoteright}Malley} } @article {Berning2021COBME, title = {Myoelectric Control and Neuromusculoskeletal Modeling: Complementary Technologies for Rehabilitation Robotics}, journal = {Current Opinion in Biomedical Engineering}, year = {2021}, pages = {100313}, abstract = {Stroke and spinal cord injury (SCI) are a leading cause of disability in the United States, and researchers have pursued using robotic devices to aid rehabilitation efforts for resulting upper-extremity impairments. To date, however, robotic rehabilitation of the upper limb has produced only limited improvement in functional outcomes compared to traditional therapy. This paper explores the potential of myoelectric control and neuromusculoskeletal modeling for robotic rehabilitation using the current state of the art of each individual field as evidence. Continuing advances in the fields of myoelectric control and neuromusculoskeletal modeling offer opportunities for further improvements of rehabilitation robot control strategies. Specifically, personalized neuromusculoskeletal models driven by a subject{\textquoteright}s electromyography signals may provide accurate predictions of the subject{\textquoteright}s muscle forces and joint moments which, when used to design novel control strategies, could yield new approaches to robotic therapy for stroke and SCI that surpass the efficacy of traditional therapy.
}, keywords = {Electromyography, neuromusculoskeletal modeling, robotic rehabilitation, upper limb motor impairment}, issn = {2468-4511}, doi = {https://doi.org/10.1016/j.cobme.2021.100313}, url = {https://www.sciencedirect.com/science/article/pii/S2468451121000532}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/BerningCOBME2021_preprint.pdf}, author = {Jeffrey Berning and Gerard E. Francisco and Shuo-Hsiu Chang and Benjamin J. Fregly and Marcia K. O{\textquoteright}Malley} } @article {1993, title = {The SE-AssessWrist for robot-aided assessment of wrist stiffness and range of motion: Development and experimental validation}, journal = {Journal of Rehabilitation and Assistive Technologies Engineering}, volume = {8}, year = {2021}, month = {04/2021}, pages = {2055668320985774}, abstract = {IntroductionPhysical human-robot interaction offers a compelling platform for assessing recovery from neurological injury; however, robots currently used for assessment have typically been designed for the requirements of rehabilitation, not assessment. In this work, we present the design, control, and experimental validation of the SE-AssessWrist, which extends the capabilities of prior robotic devices to include complete wrist range of motion assessment in addition to stiffness evaluation.MethodsThe SE-AssessWrist uses a Bowden cable-based transmission in conjunction with series elastic actuation to increase device range of motion while not sacrificing torque output. Experimental validation of robot-aided wrist range of motion and stiffness assessment was carried out with five able-bodied individuals.ResultsThe SE-AssessWrist achieves the desired maximum wrist range of motion, while having sufficient position and zero force control performance for wrist biomechanical assessment. Measurements of two-degree-of-freedom wrist range of motion and stiffness envelopes revealed that the axis of greatest range of motion and least stiffness were oblique to the conventional anatomical axes, and approximately parallel to each other.ConclusionsSuch an assessment could be beneficial in the clinic, where standard clinical measures of recovery after neurological injury are subjective, labor intensive, and graded on an ordinal scale.
}, doi = {10.1177/2055668320985774}, url = {https://doi.org/10.1177/2055668320985774}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/JRATE_2021_Erwin_SE-AssessWrist_press.pdf}, author = {Andrew Erwin and Craig G McDonald and Nicholas Moser and Marcia K O{\textquoteright}Malley} } @article {kadivar2021, title = {Single limb cable driven wearable robotic device for upper extremity movement support after traumatic brain injury}, journal = {Journal of Rehabilitation and Assistive Technologies Engineering}, volume = {8}, year = {2021}, pages = {20556683211002448}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/JRATE_2021_Kadivar_Armstrong.pdf}, author = {Kadivar, Zahra and Beck, Christopher E and Rovekamp, Roger N and O{\textquoteright}Malley, Marcia K} } @proceedings {2014, title = {Snaptics: Low-Cost Open-Source Hardware for Wearable Multi-Sensory Haptics}, year = {2021}, publisher = {IEEE}, address = {Montreal, QC, Canada}, doi = {10.1109/WHC49131.2021.9517172}, url = {https://ieeexplore.ieee.org/document/9517172/http://xplorestaging.ieee.org/ielx7/9517073/9517125/09517172.pdf?arnumber=9517172}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Snaptics_2021.pdf}, author = {Zook, Zane A. and Ozor-Ilo, Ozioma O. and Zook, Gabriel T. and O{\textquoteright}Malley, Marcia K.} } @article {9117187, title = {Syntacts: Open-Source Software and Hardware for Audio-Controlled Haptics}, journal = {IEEE Transactions on Haptics}, volume = {14}, number = {1}, year = {2021}, month = {Jan-Mar 2021}, pages = {225-233}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Syntacts.pdf}, author = {E. Pezent and B. Cambio and M. K. O{\textquoteright}Malley} } @article {murali2021vel, title = {Velocity-Domain Motion Quality Measures for Surgical Performance Evaluation and Feedback}, journal = {Journal of Medical Devices}, volume = {15}, number = {1}, year = {2021}, pages = {011107}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/med_015_01_011107.pdf}, author = {Murali, Barathwaj and Belvroy, Viony M and Pandey, Shivam and Bismuth, Jean and Byrne, Michael D and O{\textquoteright}Malley, Marcia K} } @proceedings {1978, title = {Explorations of Wrist Haptic Feedback for AR/VR Interactions with Tasbi}, year = {2020}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, keywords = {bracelet, haptics, multisensory, Virtual reality, wearables}, isbn = {9781450368193}, doi = {10.1145/3334480.3383151}, url = {https://doi.org/10.1145/3334480.3383151}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/tasbi_chi2020_20200216_compressed.pdf}, author = {Pezent, Evan and O{\textquoteright}Malley, Marcia K. and Israr, Ali and Samad, Majed and Robinson, Shea and Agarwal, Priyanshu and Benko, Hrvoje and Colonnese, Nicholas} } @proceedings {2001, title = {Importance of Wrist Movement Direction in Performing Activities of Daily Living Efficiently}, year = {2020}, publisher = {IEEE}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Moser2020EMBC_wrist_constrained_movement_0.pdf}, author = {Moser, Nicholas and O{\textquoteright}Malley, Marcia K and Erwin, Andrew} } @article {1969, title = {In the Fundamentals of Endovascular and Vascular Surgery model motion metrics reliably differentiate competency}, journal = {Journal of Vascular Surgery}, volume = {72}, number = {6}, year = {2020}, month = {12/2020}, pages = {2161-2165}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/JVS2020_Belvroy_et_al.pdf}, author = {Viony Belvroy and Barathwaj Murali and Malachi G. Sheahan and Marcia K. O{\textquoteright}Malley and Jean Bismuth} } @article {1961, title = {Multi-Sensory Stimuli Improve Distinguishability of Cutaneous Haptic Cues}, journal = {IEEE Transactions on Haptics}, volume = {13}, number = {2}, year = {2020}, month = {April-June 2020}, pages = {286-297}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Sullivan_ToH_2020_multi-sensory.pdf}, author = {Sullivan, Jennifer L and Dunkelberger, Nathan and Bradley, Joshua and Young, Joseph and Israr, Ali and Lau, Frances and Klumb, Keith and Abnousi, Freddy and O{\textquoteright}Malley, Marcia K} } @article {9031340, title = {A Myoelectric Control Interface for Upper-Limb Robotic Rehabilitation Following Spinal Cord Injury}, journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering}, volume = {28}, number = {4}, year = {2020}, month = {April}, pages = {978-987}, abstract = {Spinal cord injury (SCI) is a widespread, life-altering injury leading to impairment of sensorimotor function that, while once thought to be permanent, is now being treated with the hope of one day being able to restore function. Surface electromyography (EMG) presents an opportunity to examine and promote human engagement at the neuromuscular level, enabling new protocols for intervention that could be combined with robotic rehabilitation, particularly when robot motion or force sensing may be unusable due to the user{\textquoteright}s impairment. In this paper, a myoelectric control interface to an exoskeleton for the elbow and wrist was evaluated on a population of ten able-bodied participants and four individuals with cervical-level SCI. The ability of an EMG classifier to discern intended direction of motion in single-degree-of-freedom (DoF) and multi-DoF control modes was assessed for usability in a therapy-like setting. The classifier demonstrated high accuracy for able-bodied participants (averages over 99\% for single-DoF and near 90\% for multi-DoF), and performance in the SCI group was promising, warranting further study (averages ranging from 85\% to 95\% for single-DoF, and variable multi-DoF performance averaging around 60\%). These results are encouraging for the future use of myoelectric interfaces in robotic rehabilitation for SCI.
}, keywords = {Electromyography, injuries, Muscles, myoelectric control, pattern recognition, Rehabilitation robotics, Robot kinematics, Robot sensing systems, spinal cord injury, Wrist}, issn = {1558-0210}, doi = {10.1109/TNSRE.2020.2979743}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/TNSRE_2020_McDonald.pdf}, author = {C. G. McDonald and J. L. Sullivan and T. A. Dennis and M. K. O{\textquoteright}Malley} } @article {BHAGAT2020102502, title = {Neural activity modulations and motor recovery following brain-exoskeleton interface mediated stroke rehabilitation}, journal = {NeuroImage: Clinical}, volume = {28}, year = {2020}, pages = {102502}, abstract = {Brain-machine interfaces (BMI) based on scalp EEG have the potential to promote cortical plasticity following stroke, which has been shown to improve motor recovery outcomes. However, the efficacy of BMI enabled robotic training for upper-limb recovery is seldom quantified using clinical, EEG-based, and kinematics-based metrics. Further, a movement related neural correlate that can predict the extent of motor recovery still remains elusive, which impedes the clinical translation of BMI-based stroke rehabilitation. To address above knowledge gaps, 10 chronic stroke individuals with stable baseline clinical scores were recruited to participate in 12 therapy sessions involving a BMI enabled powered exoskeleton for elbow training. On average, 132\ {\textpm}\ 22 repetitions were performed per participant, per session. BMI accuracy across all sessions and subjects was 79\ {\textpm}\ 18\% with a false positives rate of 23\ {\textpm}\ 20\%. Post-training clinical assessments found that FMA for upper extremity and ARAT scores significantly improved over baseline by 3.92\ {\textpm}\ 3.73 and 5.35\ {\textpm}\ 4.62 points, respectively. Also, 80\% participants (7 with moderate-mild impairment, 1 with severe impairment) achieved minimal clinically important difference (MCID: FMA-UE \>5.2 or ARAT \>5.7) during the course of the study. Kinematic measures indicate that, on average, participants{\textquoteright} movements became faster and smoother. Moreover, modulations in movement related cortical potentials, an EEG-based neural correlate measured contralateral to the impaired arm, were significantly correlated with ARAT scores (ρ\ =\ 0.72, p\ \<\ 0.05) and marginally correlated with FMA-UE (ρ\ =\ 0.63, p\ =\ 0.051). This suggests higher activation of ipsi-lesional hemisphere post-intervention or inhibition of competing contra-lesional hemisphere, which may be evidence of neuroplasticity and cortical reorganization following BMI mediated rehabilitation therapy.
}, keywords = {Brain-machine interface, Clinical trial, Exoskeletons, Movement related cortical potentials, stroke rehabilitation}, issn = {2213-1582}, doi = {https://doi.org/10.1016/j.nicl.2020.102502}, url = {http://www.sciencedirect.com/science/article/pii/S2213158220303399}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/NeuroImage_2020_Bhagat_BMI_EEG_exo.pdf}, author = {Nikunj A. Bhagat and Nuray Yozbatiran and Jennifer L. Sullivan and Ruta Paranjape and Colin Losey and Zachary Hernandez and Zafer Keser and Robert Grossman and Gerard E. Francisco and Marcia K. O{\textquoteright}Malley and Jose L. Contreras-Vidal} } @article {dunkelberger2020, title = {A review of methods for achieving upper limb movement following spinal cord injury through hybrid muscle stimulation and robotic assistance}, journal = {Experimental Neurology}, year = {2020}, pages = {113274}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Dunkelberger-et-al-2020.pdf}, author = {Dunkelberger, Nathan and Schearer, Eric M and O{\textquoteright}Malley, Marcia K} } @inbook {1979, title = {Simply Grasping Simple Shapes: Commanding a Humanoid Hand with a Shape-Based Synergy}, booktitle = {Robotics Research}, year = {2020}, pages = {541{\textendash}553}, publisher = {Springer}, organization = {Springer}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/farrell2020simply.pdf}, author = {Farrell, Logan C and Dennis, Troy A and Badger, Julia and O{\textquoteright}Malley, Marcia K} } @proceedings {1982, title = {Spatially Separated Cutaneous Haptic Guidance for Training of a Virtual Sensorimotor Task}, year = {2020}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/IEEE_HS_2020_Smith_OpenWrist_CUFF_Training__shared__compressed.pdf}, author = {C. Smith and E. Pezent and M. K. O{\textquoteright}Malley} } @proceedings {1990, title = {Towards Automated Performance Assessment using Velocity-based Motion Quality Metrics}, year = {2020}, month = {11/2020}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/ISMR_2020_Murali_et_al_FinalVersion_0.pdf}, author = {Barathwaj Murali and Viony Belvroy and Shivam Pandey and Michael D. Byrne and Jean Bismuth and Marcia K. O{\textquoteright}Malley} } @proceedings {1956, title = {A Cutaneous Haptic Cue Characterization Testbed}, year = {2019}, publisher = {IEEE}, address = {Tokyo, Japan}, doi = {10.1109/WHC.2019.8816086}, url = {https://ieeexplore.ieee.org/document/8816086/http://xplorestaging.ieee.org/ielx7/8807988/8816072/08816086.pdf?arnumber=8816086}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/A_Cutaneous_Haptic_Cue_Characterization_Testbed_smaller_0.pdf}, author = {Fleck, Joshua J. and Zook, Zane A. and Andrew Low and O{\textquoteright}Malley, Marcia K.} } @proceedings {1962, title = {Design and Characterization of a Passive Instrumented Hand}, year = {2019}, month = {10/2019}, doi = {https://doi.org/10.1115/DSCC2019-9082}, url = {https://asmedigitalcollection.asme.org/DSCC/proceedings/DSCC2019/59148/V001T05A007/1070466?searchresult=1}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Instrumented_Hand_DSCC_Revised-compressed.pdf}, author = {Yousaf, Saad N and Joshi, Victoria S and Britt, John E and Rose, Chad G and O{\textquoteright}Malley, Marcia K} } @proceedings {1946, title = {Effect of Interference on Multi-Sensory Haptic Perception of Stretch and Squeeze}, year = {2019}, publisher = {IEEE}, address = {Tokyo, Japan}, doi = {10.1109/WHC.2019.8816139}, url = {https://ieeexplore.ieee.org/document/8816139/http://xplorestaging.ieee.org/ielx7/8807988/8816072/08816139.pdf?arnumber=8816139}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Effect-Interference-Zook.pdf}, author = {Zook, Zane A. and Fleck, Joshua J. and Andrew Low and O{\textquoteright}Malley, Marcia K.} } @article {losey19enabling, title = {Enabling Robots to Infer how End-Users Teach and Learn through Human-Robot Interaction}, journal = {IEEE Robotics and Automation Letters}, volume = {4}, number = {2}, year = {2019}, month = {2019}, pages = {1956-1963}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Losey_RAL2019.pdf}, author = {Losey, Dylan P and O{\textquoteright}Malley, Marcia K} } @article {o2019expert, title = {Expert Surgeons Can Smoothly Control Robotic Tools With a Discrete Control Interface}, journal = {IEEE Transactions on Human-Machine Systems}, volume = {49}, number = {4}, year = {2019}, pages = {388{\textendash}394}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/THMS2019_O\%27Malley-et-al.pdf}, author = {O{\textquoteright}Malley, Marcia K and Byrne, Michael D and Estrada, Sean and Duran, Cassidy and Schulz, Daryl and Bismuth, Jean} } @article {rose2018hybrid, title = {A Hybrid Rigid-Soft Hand Exoskeleton to Assist Functional Dexterity}, journal = {IEEE Robotics and Automation Letters}, volume = {4}, number = {1}, year = {2019}, month = {01/2019}, pages = {73-80}, issn = {2377-3766}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Rose2018RA-L.pdf}, author = {Rose, Chad and O{\textquoteright}Malley, Marcia} } @article {1940, title = {Improving short-term retention after robotic training by leveraging fixed-gain controllers}, journal = {Journal of Rehabilitation and Assistive Technologies Engineering}, volume = {6}, year = {2019}, month = {01/2019}, abstract = {IntroductionWhen developing control strategies for robotic rehabilitation, it is important that end-users who train with those strategies retain what they learn. Within the current state-of-the-art, however, it remains unclear what types of robotic controllers are best suited for promoting retention. In this work, we experimentally compare short-term retention in able-bodied end-users after training with two common types of robotic control strategies: fixed- and variable-gain controllers.MethodsOur approach is based on recent motor learning research, where reward signals are employed to reinforce the learning process. We extend this approach to now include robotic controllers, so that participants are trained with a robotic control strategy and auditory reward-based reinforcement on tasks of different difficulty. We then explore retention after the robotic feedback is removed.ResultsOverall, our results indicate that fixed-gain control strategies better stabilize able-bodied users{\textquoteright} motor adaptation than either a no controller baseline or variable-gain strategy. When breaking these results down by task difficulty, we find that assistive and resistive fixed-gain controllers lead to better short-term retention on less challenging tasks but have opposite effects on the learning and forgetting rates.ConclusionsThis suggests that we can improve short-term retention after robotic training with consistent controllers that match the task difficulty.
}, keywords = {Control systems, haptic device, motor learning, neurorehabilitation, Robot-assisted rehabilitation}, doi = {10.1177/2055668319866311}, url = {https://doi.org/10.1177/2055668319866311}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Losey2019RATE.pdf}, author = {Dylan P Losey and Laura H Blumenschein and Janelle P Clark and Marcia K O{\textquoteright}Malley} } @proceedings {1948, title = {The Influence of Cue Presentation Velocity on Skin Stretch Perception}, year = {2019}, month = {July}, keywords = {cue perceptibility, cue perception, haptic cues, Haptic interfaces, just noticeable difference, Likert surveys, method of constant stimuli, rice haptic rocker, rotational velocities, Skin, skin stretch cue presentation velocity, skin stretch cues, skin stretch perception, wearable haptic devices}, doi = {10.1109/WHC.2019.8816120}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Kim_2019_WorldHaptics_SkinStretchCueVelocity.pdf}, author = {S. Y. Kim and J. P. Clark and P. Kortum and M. K. O{\textquoteright}Malley} } @article {2019HRI, title = {Learning the Correct Robot Trajectory in Real-Time from Physical Human Interactions}, journal = {ACM Transactions on Human-Robot Interaction (THRI)}, volume = {9}, number = {1}, year = {2019}, pages = {1}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Losey_ACMTHRI_2019.pdf}, author = {Losey, Dylan P and O{\textquoteright}Malley, Marcia K} } @proceedings {2055, title = {A Robotic Platform for 3D Forelimb Rehabilitation with Rats}, year = {2019}, doi = {10.1109/ICORR.2019.8779405}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/ErwinICORR2019.pdf}, author = {Erwin, Andrew and Gallegos, Chrystine and Cao, Qilin and O{\textquoteright}Malley, Marcia K.} } @proceedings {1938, title = {On the role of wearable haptics for force feedback in teleimpedance control for dual-arm robotic teleoperation}, year = {2019}, publisher = {IEEE}, abstract = {Robotic teleoperation enables humans to safely complete exploratory procedures in remote locations for applications such as deep sea exploration or building assessments following natural disasters. Successful task completion requires meaningful dual arm robotic coordination and proper understanding of the environment. While these capabilities are inherent to humans via impedance regulation and haptic interactions, they can be challenging to achieve in telerobotic systems. Teleimpedance control has allowed impedance regulation in such applications, and bilateral teleoperation systems aim to restore haptic sensation to the operator, though often at the expense of stability or workspace size. Wearable haptic devices have the potential to apprise the operator of key forces during task completion while maintaining stability and transparency. In this paper, we evaluate the impact of wearable haptics for force feedback in teleimpedance control for dual-arm robotic teleoperation. Participants completed a peg-in-hole, box placement task, aiming to seat as many boxes as possible within the trial period. Experiments were conducted both transparent and opaque boxes. With the opaque box, participants achieved a higher number of successful placements with haptic feedback, and we saw higher mean interaction forces. Results suggest that the provision of wearable haptic feedback may increase confidence when visual cues are obscured.}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Clark_2019_ICRA_TeleimpedanceWithHaptics_0.pdf}, author = {Clark, Janelle P and Lentini, Gianluca and Barontini, Federica and Catalano, Manuel G and Bianchi, Matteo and O{\textquoteright}Malley, Marcia K} } @article {article, title = {Skin stretch haptic feedback to convey closure information in anthropomorphic, under-actuated upper limb soft prostheses}, journal = {IEEE Transactions on Haptics}, volume = {12}, number = {4}, year = {2019}, month = {2019 December}, pages = {508 - 520}, doi = {10.1109/TOH.2019.2915075}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Battaglia_ToH_2019.pdf}, author = {Battaglia, Edoardo and Clark, Janelle and Bianchi, Matteo and Catalano, Manuel and Bicchi, Antonio and O{\textquoteright}Malley, Marcia} } @article {1934, title = {Spatially Separating Haptic Guidance from Task Dynamics through Wearable Devices.}, journal = {IEEE Trans Haptics}, volume = {12}, number = {4}, year = {2019}, month = {2019 December}, pages = {581 - 593}, abstract = {Haptic devices have a high potential for delivering tailored training to novices. These devices can simulate forces associated with real-world tasks, or provide guidance forces that convey task completion and learning strategies. It has been shown, however, that providing both task forces and guidance forces simultaneously through the same haptic interface can lead to novices depending on guidance, being unable to demonstrate skill transfer, or learning the wrong task altogether. This work presents a novel solution whereby task forces are relayed via a kinesthetic haptic interface, while guidance forces are spatially separated through a cutaneous skin stretch modality. We explore different methods of delivering cutaneous based guidance to subjects in a dynamic trajectory following task. We next compare cutaneous guidance to kinesthetic guidance, as is traditional to spatially separated assistance. We further investigate the role of placing cutaneous guidance ipsilateral versus contralateral to the task force device. The efficacies of each guidance condition are compared by examining subject error and movement smoothness. Results show that cutaneous guidance can be as effective as kinesthetic guidance, making it a practical and cost-effective alternative for spatially separated assistance.
}, issn = {2329-4051}, doi = {10.1109/TOH.2019.2919281}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/pezent_toh2019.pdf}, author = {Pezent, Evan and Fani, Simone and Clark, Janelle and Bianchi, Matteo and OMalley, Marcia K} } @article {rose2018wrist, title = {Assessing Wrist Movement With Robotic Devices}, journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering}, volume = {26}, number = {8}, year = {2018}, pages = {1585{\textendash}1595}, abstract = {Robotic devices have been proposed to meet the rising need for high intensity, long duration, and goal-oriented therapy required to regain motor function after neurological injury. Complementing this application, exoskeletons can augment traditional clinical assessments through precise, repeatable measurements of joint angles and movement quality. These measures assume that exoskeletons are making accurate joint measurements with a negligible effect on movement. For the coupled and coordinated joints of the wrist and hand, the validity of these two assumptions cannot be established by characterizing the device in isolation. To examine these assumptions, we conducted three user-in-the-loop experiments with able-bodied participants. First, we compared robotic measurements to an accepted modality to determine the validity of joint- and trajectory-level measurements. Then, we compared those movements to movements without the device to investigate the effects of device dynamic properties on wrist movement characteristics. Last, we investigated the effect of the device on coordination with a redundant, coordinated pointing task with the wrist and hand. For all experiments, smoothness characteristics were preserved in the robotic kinematic measurement and only marginally impacted by robot dynamics, validating the exoskeletons for use as assessment devices. Stemming from these results, we propose design guidelines for exoskeletal assessment devices.
}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/rose2018ieee-wrist.pdf}, author = {Rose, Chad G and Pezent, Evan and Kann, Claudia K and Deshpande, Ashish D and O{\textquoteright}Malley, Marcia K} } @proceedings {1915, title = {A Bowden Cable-Based Series Elastic Actuation Module for Assessing the Human Wrist}, year = {2018}, month = {10/2018}, publisher = {ASME}, address = {Atlanta, GA}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/EwrinDSCC2018-8963.pdf}, author = {Andrew Erwin and Nick Moser and Craig. G. McDonald and Marcia K. O{\textquoteright}Malley} } @article {1859, title = {Closure to {\textquotedblleft}A review of intent detection, arbitration, and communication aspects of shared control for physical human-robot interaction"}, journal = {ASME Applied Mechanics Reviews}, volume = {70}, number = {1}, year = {2018}, month = {02/2018}, abstract = {In their discussion article on our review paper, Professors James Schmiedeler and Patrick Wensing have provided an insightful and informative perspective of the roles of intent detection, arbitration, and communication as three pillars of a framework for the implementation of shared control in physical human{\textendash}robot interaction (pHRI). The authors both have significant expertise and experience in robotics, bipedal walking, and robotic rehabilitation. Their commentary introduces commonalities between the themes of the review paper and issues in locomotion with the aid of an exoskeleton or lower-limb prostheses, and presents several important topics that warrant further exploration. These include mechanical design as it pertains to the physical coupling between human and robot, modeling the human to improve intent detection and the arbitration of control, and finite-state machines as an approach for implementation. In this closure, we provide additional thoughts and discussion of these topics as they relate to pHRI.
}, doi = {10.1115/1.4039225}, url = {http://appliedmechanicsreviews.asmedigitalcollection.asme.org/article.aspx?articleID=2672398}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/amr_2018_closure.pdf}, author = {Dylan P. Losey and Craig G. McDonald and Edoardo Battaglia and Marcia K. O{\textquoteright}Malley} } @proceedings {1913, title = {Conveying Language Through Haptics: A Multi-sensory Approach}, year = {2018}, month = {10/2018}, publisher = {ACM}, address = {Singapore}, keywords = {haptics, multi-sensory, speech, wearable}, isbn = {978-1-4503-5967-2}, doi = {10.1145/3267242.3267244}, url = {http://doi.acm.org/10.1145/3267242.3267244}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/NathanDunkelberger_ISWC.pdf}, author = {Dunkelberger, Nathan and Sullivan, Jenny and Bradley, Joshua and Walling, Nickolas P and Manickam, Indu and Dasarathy, Gautam and Israr, Ali and Lau, Frances W. Y. and Klumb, Keith and Knott, Brian and Abnousi, Freddy and Baraniuk, Richard and O{\textquoteright}Malley, Marcia K} } @proceedings {1920, title = {Cycloidal Geartrain In-Use Efficiency Study}, year = {2018}, month = {08/2018}, publisher = {American Society of Mechanical Engineers}, address = {Quebec, Canada}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Farrell2018IDETC.pdf}, author = {Farrell, Logan C and Holley, James and Bluethmann, William and O{\textquoteright}Malley, Marcia K} } @proceedings {1935, title = {Effects of Latency and Refresh Rate on Force Perception via Sensory Substitution by Force-Controlled Skin Deformation Feedback}, year = {2018}, publisher = {IEEE}, address = {Brisbane, QLD}, abstract = {Latency and refresh rate are known to adversely affect human force perception in bilateral teleoperators and virtual environments using kinesthetic force feedback, motivating the use of sensory substitution of force. The purpose of this study is to quantify the effects of latency and refresh rate on force perception using sensory substitution by skin deformation feedback. A force-controlled skin deformation feedback device was attached to a 3-degree-of-freedom kinesthetic force feedback device used for position tracking and gravity support. A human participant study was conducted to determine the effects of latency and refresh rate on perceived stiffness and damping with skin deformation feedback. Participants compared two virtual objects: a comparison object with stiffness or damping that could be tuned by the participant, and a reference object with either added latency or reduced refresh rate. Participants modified the stiffness or damping of the tunable object until it resembled the stiffness or damping of the reference object. We found that added latency and reduced refresh rate both increased perceived stiffness but had no effect on perceived damping. Specifically, participants felt significantly different stiffness when the latency exceeded 300 ms and the refresh rate dropped below 16.6 Hz. The impact of latency and refresh rate on force perception via skin deformation feedback was significantly less than what has been previously shown for kinesthetic force feedback.
}, doi = {10.1109/ICRA.2018.8462883}, url = {https://ieeexplore.ieee.org/document/8462883/http://xplorestaging.ieee.org/ielx7/8449910/8460178/08462883.pdf?arnumber=8462883}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Zook\%20et\%20al.\%20-\%20Effects\%20of\%20Latency\%20and\%20Refresh\%20Rate\%20on\%20Force\%20Perce.pdf}, author = {Zook, Zane A. and Okamura, Allison M. and Kamikawa, Yasuhisa} } @article {PMID:28583735, title = {Electromagnetic tracking of flexible robotic catheters enables "assisted navigation" and brings automation to endovascular navigation in an in vitro study}, journal = {Journal of vascular surgery}, volume = {67}, number = {4}, year = {2018}, month = {06/2017}, pages = {1274{\textendash}1281}, issn = {0741-5214}, doi = {10.1016/j.jvs.2017.01.072}, url = {https://doi.org/10.1016/j.jvs.2017.01.072}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Schwein2017JVS.pdf}, author = {Schwein, Adeline and Kramer, Benjamin and Chinnadurai, Ponraj and Virmani, Neha and Walker, Sean and O{\textquoteright}Malley, Marcia and Lumsden, Alan B and Bismuth, Jean} } @article {8291748, title = {Evaluation of Velocity Estimation Methods Based on their Effect on Haptic Device Performance}, journal = {IEEE/ASME Transactions on Mechatronics}, volume = {23}, number = {2}, year = {2018}, pages = {604-613}, abstract = {This paper comparatively evaluates the effect of real-time velocity estimation methods on passivity and fidelity of virtual walls implemented using haptic interfaces. Impedance width, or Z-width is a fundamental measure of performance in haptic devices. Limited accuracy of velocity estimates from position encoder data is an impediment in improving the Z- width in haptic interfaces. We study the efficacy of Levant{\textquoteright}s differentiator as a velocity estimator, to allow passive implementation of higher stiffness virtual walls as compared to some of the commonly used velocity estimators in the field of haptics. We first experimentally demonstrate feasibility of Levant{\textquoteright}s differentiator as a velocity estimator for haptics applications by comparing Z-width performance achieved with Levant{\textquoteright}s differentiator and commonly used Finite Difference Method (FDM) cascaded with a lowpass filter. A novel Z-width plotting technique combining passivity and fidelity of haptic rendering is proposed, and used to compare the haptic device performance obtained with Levant{\textquoteright}s differentiator, FDM+lowpass filter, First Order Adaptive Windowing and Kalman filter based velocity estimation methods. Simulations and experiments conducted on a custom single degree of freedom haptic device demonstrate that the stiffest virtual walls are rendered with velocity estimated using Levant{\textquoteright}s differentiator, and highest wall rendering fidelity is achieved by First Order Adaptive Windowing based velocity estimation scheme.
}, keywords = {Estimation, Frequency division multiplexing, Haptic interfaces, Impedance, Kalman filters, Performance evaluation, Rendering (computer graphics)}, issn = {1083-4435}, doi = {10.1109/TMECH.2018.2805863}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/chawda2018ieee.pdf}, author = {V. Chawda and O. Celik and M. K. O{\textquoteright}Malley} } @article {8304762, title = {The hBracelet: a wearable haptic device for the distributed mechanotactile stimulation of the upper limb}, journal = {IEEE Robotics and Automation Letters}, volume = {3}, number = {3}, year = {2018}, month = {2018}, pages = {2198-2205}, abstract = {Haptic interfaces are mechatronic devices designed to render tactile sensations; although they are typically based on robotic manipulators external to the human body, recently, interesting wearable solutions have been presented. Towards a more realistic feeling of virtual and remote environment interactions, we propose a novel wearable skin stretch device for the upper limb called "hBracelet." It consists of two main parts coupled with a linear actuator. Each part contains two servo actuators that move a belt. The device is capable of providing distributed mechanotactile stimulation on the arm by controlling the tension and the distance of the two belts in contact with the skin. When the motors spin in opposite directions, the belt presses into the user{\textquoteright}s arm, while when they spin in the same direction, the belt applies a shear force to the skin. Moreover, the linear actuator exerts longitudinal cues on the arm by moving the two parts of the device. In this work we illustrate the mechanical structure, working principle, and control strategies of the proposed wearable haptic display. We also present a qualitative experiment in a teleoperation scenario as a case study to demonstrate the effectiveness of the proposed haptic interface and to show how a human can take advantage of multiple haptic stimuli provided at the same time and on the same body area. The results show that the device is capable of successfully providing information about forces acting at the remote site, thus improving telepresence.
}, keywords = {Actuators, Belts, Force, Haptic interfaces, Haptics and haptic interfaces, Human-Centered Robotics, Pulleys, Robots, Skin, Telerobotics and Teleoperation, Wearable Robots}, doi = {10.1109/LRA.2018.2810958}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/meli2018ieee.pdf}, author = {L. Meli and I. Hussain and M. Aurilio and M. Malvezzi and M. O{\textquoteright}Malley and D. Prattichizzo} } @proceedings {1902, title = {Improving Perception Accuracy with Multi-sensory Haptic Cue Delivery}, volume = {II}, year = {2018}, month = {June 13-16}, pages = {289-301}, publisher = {Springer International Publishing}, address = {Pisa, Italy}, abstract = {This paper presents a novel, wearable, and multi-sensory haptic feedback system intended to support the transmission of large sets of haptic cues that are accurately perceived by the human user. Previous devices have focused on the optimization of haptic cue transmission using a single modality and have typically employed arrays of haptic tactile actuators to maximize information throughput to a user. However, when large cue sets are to be transmitted, perceptual interference between transmitted cues can decrease the efficacy of single-sensory systems. Therefore, we present MISSIVE (Multi-sensory Interface of Stretch, Squeeze, and Integrated Vibration Elements), a wearable system that conveys multi-sensory haptic cues to the user{\textquoteright}s upper arm, allowing for increased perceptual accuracy compared to a single-sensory vibrotactile array of a comparable size, conveying the same number of cues. Our multi-sensory haptic cues are comprised of concurrently rendered, yet perceptually distinct elements: radial squeeze, lateral skin stretch, and localized cutaneous vibration. Our experiments demonstrate that our approach can increase perceptual accuracy compared to a single-sensory vibrotactile system of comparable size and that users prefer MISSIVE.
}, isbn = {978-3-319-93399-3}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/dunkelberger\%202018\%20eurohaptics\%20compressed.pdf}, author = {Dunkelberger, Nathan and Bradley, Joshua and Sullivan, Jennifer L. and Israr, Ali and Lau, Frances and Klumb, Keith and Abnousi, Freddy and O{\textquoteright}Malley, Marcia K.}, editor = {Prattichizzo, Domenico and Shinoda, Hiroyuki and Tan, Hong Z. and Ruffaldi, Emanuele and Frisoli, Antonio} } @proceedings {losey2018include, title = {Including Uncertainty when Learning from Human Corrections}, year = {2018}, month = {09/2018}, address = {Zurich, Switzerland}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Losey2018includinguncertainty.pdf}, author = {Losey, Dylan P and O{\textquoteright}Malley, Marcia K} } @proceedings {1862, title = {Learning from Physical Human Corrections, One Feature at a Time}, year = {2018}, month = {03/2018}, publisher = {ACM/IEEE}, address = {Chicago, USA}, abstract = {We focus on learning robot objective functions from human guidance: specifically, from physical corrections provided by the person while the robot is acting. Objective functions are typically parametrized in terms of features, which capture aspects of the task that might be important. When the person intervenes to correct the robot{\textquoteright}s behavior, the robot should update its understanding of which features matter, how much, and in what way. Unfortunately, real users do not provide optimal corrections that isolate exactly what the robot was doing wrong. Thus, when receiving a correction, it is difficult for the robot to determine which features the person meant to correct, and which features were changed unintentionally. In this paper, we propose to improve the efficiency of robot learning during physical interactions by reducing unintended learning. Our approach allows the human-robot team to focus on learning one feature at a time, unlike state-of-the-art techniques that update all features at once. We derive an online method for identifying the single feature which the human is trying to change during physical interaction, and experimentally compare this one-at-a-time approach to the all-at-once baseline in a user study. Our results suggest that users teaching one-at-a-time perform better, especially in tasks that require changing multiple features.
}, doi = {10.1145/3171221.3171267}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Losey_HRI2018.pdf}, author = {Andrea Bajcsy and Dylan P. Losey and Marcia K. O{\textquoteright}Malley and Anca D. Dragan} } @article {1815, title = {Quantitative testing of fMRI-compatibility of an electrically active mechatronic device for robot-assisted sensorimotor protocols}, journal = {IEEE Transactions on Biomedical Engineering}, volume = {65}, number = {7}, year = {2018}, pages = {1595-1606}, doi = {10.1109/TBME.2017.2741346}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8012485\&tag=1}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Farrens2018\%20-\%20Quantitative\%20testing\%20fMRI-comp.pdf}, author = {Farrens, A.J. and Zonnino, A. and Erwin,Andrew and O{\textquoteright}Malley, M.K. and Johnson, C.L. and Ress, D. and Fabrizio Sergi} } @article {8305478, title = {Reflection on System Dynamics Principles Improves Student Performance in Haptic Paddle Labs}, journal = {IEEE Transactions on Education}, volume = {61}, number = {3}, year = {2018}, month = {08/2018}, pages = {245-252}, keywords = {abstract conceptualization, CE, computer aided instruction, concrete experience, educational courses, haptic devices, Haptic interfaces, haptics, lab report grades, laboratory, laboratory exercises, learning cycle, learning outcomes, low-cost educational tools, Mechanical engineering, mechanical engineering computing, mechanical engineering curricula, mechanical engineering curriculum, Mechatronics, mechatronics content, multiple student GPA quartiles, Performance evaluation, reflection, reflection phase, reflective curriculum, reflective observation, standard haptic paddle lab curriculum, standard nonreflective curriculum, Standards, student performance improvement, System dynamics, system dynamics principles, Tools, undergraduate, virtual environment rendering}, issn = {0018-9359}, doi = {10.1109/TE.2018.2804327}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Rose2018ieee-reflection.pdf}, author = {C. G. Rose and C. G. McDonald and J. P. Clark and M. K. O{\textquoteright}Malley} } @article {1858, title = {A review of intent detection, arbitration, and communication aspects of shared control for physical human-robot interaction}, journal = {ASME Applied Mechanics Reviews}, volume = {70}, number = {1}, year = {2018}, month = {02/2018}, abstract = {As robotic devices are applied to problems beyond traditional manufacturing and industrial settings, we find that interaction between robots and humans, especially physical interaction, has become a fast developing field. Consider the application of robotics in healthcare, where we find telerobotic devices in the operating room facilitating dexterous surgical procedures, exoskeletons in the rehabilitation domain as walking aids and upper-limb movement assist devices, and even robotic limbs that are physically integrated with amputees who seek to restore their independence and mobility. In each of these scenarios, the physical coupling between human and robot, often termed physical human robot interaction (pHRI), facilitates new human performance capabilities and creates an opportunity to explore the sharing of task execution and control between humans and robots. In this review, we provide a unifying view of human and robot sharing task execution in scenarios where collaboration and cooperation between the two entities are necessary, and where the physical coupling of human and robot is a vital aspect. We define three key themes that emerge in these shared control scenarios, namely, intent detection, arbitration, and feedback. First, we explore methods for how the coupled pHRI system can detect what the human is trying to do, and how the physical coupling itself can be leveraged to detect intent. Second, once the human intent is known, we explore techniques for sharing and modulating control of the coupled system between robot and human operator. Finally, we survey methods for informing the human operator of the state of the coupled system, or the characteristics of the environment with which the pHRI system is interacting. At the conclusion of the survey, we present two case studies that exemplify shared control in pHRI systems, and specifically highlight the approaches used for the three key themes of intent detection, arbitration, and feedback for applications of upper limb robotic rehabilitation and haptic feedback from a robotic prosthesis for the upper limb.
}, doi = {DOI: 10.1115/1.4039145}, url = {http://appliedmechanicsreviews.asmedigitalcollection.asme.org/article.aspx?articleID=2671581}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/amr_2018_review.pdf}, author = {Dylan P. Losey and Craig G. McDonald and Edoardo Battaglia and Marcia K. O{\textquoteright}Malley} } @proceedings {1917, title = {The rice haptic rocker: Altering the perception of skin stretch through mapping and geometric design}, year = {2018}, month = {03/2018}, pages = {192-197}, publisher = {IEEE}, address = {San Francisco, CA}, abstract = {Skin stretch haptic devices are well-suited for transmitting information through touch, a promising avenue in prosthetic research, addressing the lack of feedback in myoelectric designs. Rocker-based skin stretch devices have been proposed for sensory substitution and navigational feedback, but the designs vary in their geometry. Other works create torsional stretch, and utilize nonlinear mappings to enhance perception. This work investigates parameters of rocker geometry and mapping functions, and how they impact user perception. We hypothesize that perceptual changes are dependent on the choice of stretch increment sizes over the range of motion. The rocker geometry is varied with an offset between the rotational and geometric axes, and three rocker designs are evaluated during a targeting task implemented with a nonlinear or linear mapping. The rockers with no offset and a positive offset (wide) perform better than the negative offset (narrow) case, though the mapping method does not affect target accuracy.
}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Clark_2018HapticSymposium.pdf}, author = {Clark, Janelle P and Kim, Sung Y and O{\textquoteright}Malley, Marcia K} } @proceedings {1901, title = {The Rice Haptic Rocker: Comparing Longitudinal and Lateral Upper-Limb Skin Stretch Perception}, volume = {II}, year = {2018}, month = {06/2018}, pages = {125-134}, publisher = {Springer International Publishing}, address = {Pisa, Italy}, abstract = {Skin stretch, when mapped to joint position, provides haptic feedback using a mechanism similar to our sense of proprioception . Rocker-type skin stretch devices typically actuate in the lateral direction of the arm, though during limb movement stretch about joint angles is in the longitudinal direction. In this paper, human perceptual performance in a target-hitting task is compared for two orientations of the Rice Haptic Rocker. The longitudinal direction is expected to be more intuitive due to the biological similarities, creating a more effective form of haptic feedback. The rockers are placed on the upper arm, and convey the position of a cursor among five vertically aligned targets. The longitudinal orientation results in smaller errors compared to the lateral case. Additionally, the outer targets were reached with less error than the inner targets for the longitudinal rocker. This result suggests longitudinal stretch is more easily discerned than laterally oriented stretch.
}, isbn = {978-3-319-93399-3}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/clark\%202018\%20eurohaptics\%20reduced.pdf}, author = {Clark, Janelle P. and Kim, Sung Y. and O{\textquoteright}Malley, Marcia K.}, editor = {Prattichizzo, Domenico and Shinoda, Hiroyuki and Tan, Hong Z. and Ruffaldi, Emanuele and Frisoli, Antonio} } @proceedings {1921, title = {Separating haptic guidance from task dynamics: A practical solution via cutaneous devices}, year = {2018}, month = {03/2018}, publisher = {IEEE}, address = {San Francisco, CA}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/pezent2018hs.pdf}, author = {Pezent, Evan and Fani, Simone and Bradley, Joshua and Bianchi, Matteo and O{\textquoteright}Malley, Marcia K} } @proceedings {1903, title = {Toward improved surgical training: Delivering smoothness feedback using haptic cues}, year = {2018}, month = {03/2018}, pages = {241-246}, publisher = {IEEE}, address = {San Francisco, CA}, abstract = {Surgery is a challenging domain for motor skill acquisition, and compounding this difficulty is the often delayed and qualitative nature of feedback that is provided to trainees. In this paper, we explore the effectiveness of providing real-time feedback of movement smoothness, a characteristic associated with skilled and coordinated movement, via a vibrotactile cue. Subjects performed a mirror-tracing task that requires coordination and dexterity similar in nature to that required in endovascular surgery. Movement smoothness, measured by spectral arc length, a frequency-domain measure of movement smoothness, was encoded in a vibrotactile cue. Performance of the mirror tracing task with smoothness-based feedback was compared to position-based feedback (where the subject was alerted when they moved outside the path boundary) and to a no-feedback control condition. Although results of this pilot study failed to indicate a statistically significant effect of smoothness-based feedback on performance, subjects receiving smoothness-based feedback altered their task completion strategies to improve speed and accuracy, while those receiving position-based feedback or no feedback only improved in terms of increased accuracy. In tasks such as surgery where both speed and accuracy are vital to positive patient outcomes, the provision of smoothness-based feedback to the surgeon has the potential to positively influence performance.
}, keywords = {biomechanics, biomedical education, computer based training, coordinated movement, delayed nature, dexterity, Feedback, frequency-domain measure, haptic cues, Haptic interfaces, Measurement, medical computing, mirror tracing task, mirror-tracing task, Mirrors, motor skill acquisition, movement smoothness, Navigation, qualitative nature, real-time feedback, skilled movement, smoothness-based feedback, spectral arc length, surgery, surgical training, Task analysis, training, vibrotactile cue}, doi = {10.1109/HAPTICS.2018.8357183}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/jantscher\%202018\%20ieee.pdf}, author = {W. H. Jantscher and S. Pandey and P. Agarwal and S. H. Richardson and B. R. Lin and M. D. Byrne and M. K. O{\textquoteright}Malley} } @article {1853, title = {Trajectory deformations from physical human{\textendash}robot interaction}, journal = {IEEE Transactions on Robotics}, volume = {34}, number = {1}, year = {2018}, month = {02/2018}, pages = {126-138}, abstract = {Robots are finding new applications where physical interaction with a human is necessary, such as manufacturing, healthcare, and social tasks. Accordingly, the field of physical human{\textendash}robot interaction (pHRI) has leveraged impedance control approaches, which support compliant interactions between human and robot. However, a limitation of traditional impedance control is that{\textemdash}despite provisions for the human to modify the robot{\textquoteright}s current trajectory{\textemdash}the human cannot affect the robot{\textquoteright}s future desired trajectory through pHRI. In this paper, we present an algorithm for physically interactive trajectory deformations which, when combined with impedance control, allows the human to modulate both the actual and desired trajectories of the robot. Unlike related works, our method explicitly deforms the future desired trajectory based on forces applied during pHRI, but does not require constant human guidance. We present our approach and verify that this method is compatible with traditional impedance control. Next, we use constrained optimization to derive the deformation shape. Finally, we describe an algorithm for real-time implementation, and perform simulations to test the arbitration parameters. Experimental results demonstrate reduction in the human{\textquoteright}s effort and improvement in the movement quality when compared to pHRI with impedance control alone.
}, doi = {10.1109/TRO.2017.2765335}, url = {http://ieeexplore.ieee.org/document/8115323/}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Losey_TRO_2018.pdf}, author = {Dylan P. Losey and Marcia K. O{\textquoteright}Malley} } @proceedings {1828, title = {A Ball and Beam Module for a Haptic Paddle Education Platform}, year = {2017}, month = {10/2017}, publisher = {ASME}, address = {Tysons, VA}, abstract = {Rehabilitation exoskeletons may make use of myoelectric control to restore in patients with significant motor impairment following a spinal cord injury (SCI) a sense of volitional control over their limb - a crucial component for recovery of movement. Little investigation has been done into the feasibility of using surface electromyography (sEMG) as an exoskeleton control interface for SCI patients, whose impairment manifests in a highly variable way across the patient population. We have demonstrated that by using only a small subset of features extracted from eight bipolar electrodes recording on the upper arm and forearm muscles, we can achieve high predictive accuracy for the intended direction of motion. Five healthy subjects and two SCI subjects performed voluntary isometric contractions while wearing an exoskeleton for the wrist and elbow joints, generating six distinct single and multi-DoF motions in a total of sixteen possible directions. Using linear discriminant analysis, classification performance was then evaluated using randomly selected holdout test data from the same recording session. Commonalities across subjects, both healthy and SCI, were analyzed at the levels of selected features and the values of commonly selected features. Future work will be to investigate group-specific classification of SCI subjects{\textquoteright} intended movements for use in the real-time control of a rehabilitation exoskeleton.
}, issn = {978-1-5386-2296-4}, doi = {10.1109/ICORR.2017.8009240}, url = {http://ieeexplore.ieee.org/abstract/document/8009240/}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/mcdonald_2017_characterization.pdf}, author = {McDonald, Craig G and Dennis, Troy A and O{\textquoteright}Malley, Marcia K} } @proceedings {1923, title = {Combining functional electrical stimulation and a powered exoskeleton to control elbow flexion}, year = {2017}, month = {11/2017}, pages = {87-88}, keywords = {Elbow, elbow flexion, Exoskeletons, extension trajectory, functional electrical stimulation, hybrid FES, hybrid system, Iron, medical robotics, Muscles, neuromuscular stimulation, Patient rehabilitation, robotic exoskeleton system, Robots, Torque, Trajectory, upper-limb paralysis}, doi = {10.1109/WEROB.2017.8383860}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Wolf2017werob.pdf}, author = {D. Wolf and N. Dunkelberger and C. G. McDonald and K. Rudy and C. Beck and M. K. O{\textquoteright}Malley and E. Schearer} } @proceedings {1820, title = {Design and characterization of the OpenWrist: A robotic wrist exoskeleton for coordinated hand-wrist rehabilitation}, year = {2017}, month = {07/2017}, publisher = {IEEE}, address = {London, UK}, abstract = {Robotic devices have been clinically verified for use in long duration and high intensity rehabilitation needed for motor recovery after neurological injury. Targeted and coordinated hand and wrist therapy, often overlooked in rehabilitation robotics, is required to regain the ability to perform activities of daily living. To this end, a new coupled hand-wrist exoskeleton has been designed. This paper details the design of the wrist module and several human-related considerations made to maximize its potential as a coordinated hand-wrist device. The serial wrist mechanism has been engineered to facilitate donning and doffing for impaired subjects and to insure compatibility with the hand module in virtual and assisted grasping tasks. Several other practical requirements have also been addressed, including device ergonomics, clinician-friendliness, and ambidextrous reconfigurability. The wrist module{\textquoteright}s capabilities as a rehabilitation device are quantified experimentally in terms of functional workspace and dynamic properties. Specifically, the device possesses favorable performance in terms of range of motion, torque output, friction, and closed-loop position bandwidth when compared with existing devices. The presented wrist module{\textquoteright}s performance and operational considerations support its use in a wide range of future clinical investigations.
}, isbn = {978-1-5386-2296-4}, doi = {10.1109/ICORR.2017.8009333}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/0263_0.pdf}, author = {Pezent, Evan and Rose, Chad G. and Deshpande, Ashish D and O{\textquoteright}Malley, Marcia K} } @proceedings {1811, title = {The Effect of Robot Dynamics on Smoothness during Wrist Pointing}, year = {2017}, month = {08/2017}, publisher = {IEEE}, address = {London, England}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Erwin2017\%20-\%20Robot\%20impacts\%20movements.pdf}, author = {Erwin,Andrew and Pezent,Evan and Bradley,Joshua and O{\textquoteright}Malley, M.K.} } @article {1798, title = {Effects of assist-as-needed upper extremity robotic therapy after incomplete spinal cord injury: a parallel-group controlled trial}, journal = {Frontiers in Neurobotics}, volume = {11}, number = {26}, year = {2017}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/fnbot-11-00026.pdf}, author = {John M. Frullo and Jared Elinger and Ali Utku Pehlivan and Kyle Fitle and Kathryn Nedley and Gerard Francisco and Fabrizio Sergi and Marcia K. O{\textquoteright}Malley} } @proceedings {1821, title = {Effects of Discretization on the K-Width of Series Elastic Actuators}, year = {2017}, month = {05/2017}, pages = {421-426}, publisher = {IEEE}, address = {Singapore}, abstract = {Rigid haptic devices enable humans to physically interact with virtual environments, and the range of impedances that can be safely rendered using these rigid devices is quantified by the Z-Width metric. Series elastic actuators (SEAs) similarly modulate the impedance felt by the human operator when interacting with a robotic device, and, in particular, the robot{\textquoteright}s perceived stiffness can be controlled by changing the elastic element{\textquoteright}s equilibrium position. In this paper, we explore the K-Width of SEAs, while specifically focusing on how discretization inherent in the computer-control architecture affects the system{\textquoteright}s passivity. We first propose a hybrid model for a single degree-of-freedom (DoF) SEA based on prior hybrid models for rigid haptic systems. Next, we derive a closed-form bound on the K-Width of SEAs that is a generalization of known constraints for both rigid haptic systems and continuous time SEA models. This bound is first derived under a continuous time approximation, and is then numerically supported with discrete time analysis. Finally, experimental results validate our finding that large pure masses are the most destabilizing operator in human-SEA interactions, and demonstrate the accuracy of our theoretical K-Width bound.
}, isbn = {978-1-5090-4633-1}, issn = {978-1-5090-4633-1}, doi = {10.1109/ICRA.2017.7989054}, url = {http://ieeexplore.ieee.org/abstract/document/7989054/}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Losey_ICRA_2017.pdf}, author = {Dylan P. Losey and Marcia K. O{\textquoteright}Malley} } @proceedings {1884, title = {On the Efficacy of Isolating Shoulder and Elbow Movements with a Soft, Portable, and Wearable Robotic Device}, volume = {16}, year = {2017}, pages = {89-94}, publisher = {Springer International Publishing}, address = {Springer, Cham}, abstract = {Treatment intensity has a profound effect on motor recovery following neurological injury. The use of robotics has potential to automate these labor-intensive therapy procedures that are typically performed by physical therapists. Further, the use of wearable robotics offers an aspect of portability that may allow for rehabilitation outside the clinic. The authors have developed a soft, portable, lightweight upper extremity wearable robotic device to provide motor rehabilitation of patients with affected upper limbs due to traumatic brain injury (TBI). A key feature of the device demonstrated in this paper is the isolation of shoulder and elbow movements necessary for effective rehabilitation interventions. Herein is presented a feasibility study with one subject and demonstration of the device{\textquoteright}s ability to provide safe, comfortable, and controlled upper extremity movements. Moreover, it is shown that by decoupling shoulder and elbow motions, desired isolated joint actuation can be achieved.
}, isbn = {978-3-319-46532-6}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/kadivar2016werob.pdf}, author = {Kadivar, Zahra and Beck, Christopher E. and Rovekamp, Roger N. and O{\textquoteright}Malley, Marcia K. and Joyce, Charles A.}, editor = {Gonz{\'a}lez-Vargas, Jos{\'e} and Ib{\'a}{\~n}ez, Jaime and Contreras-Vidal, Jose L. and van der Kooij, Herman and Pons, Jos{\'e} Luis} } @proceedings {1818, title = {Estimating anatomical wrist joint motion with a robotic exoskeleton}, year = {2017}, month = {07/2017}, publisher = {IEEE}, address = {London, UK}, abstract = {Robotic exoskeletons can provide the high intensity, long duration targeted therapeutic interventions required for regaining motor function lost as a result of neurological injury. Quantitative measurements by exoskeletons have been proposed as measures of rehabilitative outcomes. Exoskeletons, in contrast to end effector designs, have the potential to provide a direct mapping between human and robot joints. This mapping rests on the assumption that anatomical axes and robot axes are aligned well, and that movement within the exoskeleton is negligible. These assumptions hold well for simple one degree-of-freedom joints, but may not be valid for multi-articular joints with unique musculoskeletal properties such as the wrist. This paper presents an experiment comparing robot joint kinematic measurements from an exoskeleton to anatomical joint angles measured with a motion capture system. Joint-space position measurements and task-space smoothness metrics were compared between the two measurement modalities. The experimental results quantify the error between joint-level position measurements, and show that exoskeleton kinematic measurements preserve smoothness characteristics found in anatomical measures of wrist movements.
}, issn = {978-1-5386-2296-4}, doi = {10.1109/ICORR.2017.8009450}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Rose_2017_Estimating.pdf}, author = {Rose, Chad G. and Kann, Claudia K and Deshpande, Ashish D and O{\textquoteright}Malley, Marcia K} } @proceedings {1816, title = {Improving robotic stroke rehabilitation by incorporating neural intent detection: Preliminary results from a clinical trial}, year = {2017}, month = {07/2018}, publisher = {IEEE}, address = {London, UK}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Sullivan_ICORR\%202017_BMI\%20Exo.pdf}, author = {Sullivan, J.L. and Bhagat, N.A. and Yozbatiran, N. and Paranjape, R. and Losey, C.G. and Grossman, R.G. and Contreras-Vidal, J.L. and Francisco, G.E. and O{\textquoteright}Malley, M.K.} } @article {1809, title = {Kinesthetic feedback during 2DOF wrist movements via a novel MR-compatible robot}, journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering}, volume = {25}, number = {9}, year = {2017}, pages = {1489-1499}, doi = {10.1109/TNSRE.2016.2634585}, url = {http://ieeexplore.ieee.org/document/7763863/}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Erwin2017\%20-\%20MR\%20SoftWrist_0.pdf}, author = {Erwin,Andrew and O{\textquoteright}Malley, M.K. and Ress, D. and Fabrizio Sergi} } @proceedings {1830, title = {Learning Robot Objectives from Physical Human Interaction}, year = {2017}, month = {11/2017}, pages = {217-226}, publisher = {PMLR}, address = {Mountain View, CA}, abstract = {When humans and robots work in close proximity, physical interaction is inevitable. Traditionally, robots treat physical interaction as a disturbance, and resume their original behavior after the interaction ends. In contrast, we argue that physical human interaction is informative: it is useful information about how the robot should be doing its task. We formalize learning from such interactions as a dynamical system in which the task objective has parameters that are part of the hidden state, and physical human interactions are observations about these parameters. We derive an online approximation of the robot{\textquoteright}s optimal policy in this system, and test it in a user study. The results suggest that learning from physical interaction leads to better robot task performance with less human effort.
}, keywords = {learning from demonstration, physical human-robot interaction}, url = {http://proceedings.mlr.press/v78/bajcsy17a.html}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/CoRL_2017.pdf}, author = {Andrea Bajcsy and Dylan P. Losey and Marcia K. O{\textquoteright}Malley and Anca D. Dragan} } @proceedings {1795, title = {The Rice Haptic Rocker: skin stretch haptic feedback with the Pisa/IIT SoftHand}, year = {2017}, month = {06/2017}, publisher = {IEEE}, address = {Munich, Germany}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/CameraReady.pdf}, author = {Edoardo Battaglia and Janelle P. Clark and Matteo Bianchi and Manuel G. Catalano and Antonio Bicchi and Marcia K. O{\textquoteright}Malley} } @article {PMID:28857769, title = {Robot-Assisted Training of Arm and Hand Movement Shows Functional Improvements for Incomplete Cervical Spinal Cord Injury}, journal = {American Journal of Physical Medicine \& Rehabilitation}, volume = {96}, number = {10}, year = {2017}, month = {10/2017}, pages = {S171{\textemdash}S177}, issn = {0894-9115}, doi = {10.1097/phm.0000000000000815}, url = {https://doi.org/10.1097/PHM.0000000000000815}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/francisco2017AJPRM.pdf}, author = {Francisco, Gerard E and Yozbatiran, Nuray and Berliner, Jeffrey and O'Malley, Marcia K and Pehlivan, Ali Utku and Kadivar, Zahra and Fitle, Kyle and Boake, Corwin} } @proceedings {1892, title = {Simply Grasping Simple Shapes: Commanding a Humanoid Hand with a Shape-Based Synergy}, year = {2017}, month = {12/2017}, address = {Puerto Varas, Chile}, abstract = {Despite rapid advancements in dexterity and mechanical design, the utility of humanoid robots outside of a controlled laboratory setting is limited in part due to the complexity involved in programming robots to grasp common objects. There exists a need for an efficient method to command high degree-of-freedom (DoF) position-controlled dexterous manipulators to grasp a range of objects such that explicit models are not needed for every interaction. The authors propose a method termed geometrical synergies that, similar to the neuroscience concept of postural synergies, aims to decrease the commanded DoF of the humanoid hand. In the geometrical synergy approach, the method relies on grasp design based on intuitive measurements of the object to be grasped, in contrast to postural synergy methods that focus on the principal components of human grasps to determine robot hand joint commands. For this paper, a synergy was designed to grasp cylinder-shaped objects. Using the SynGrasp toolbox, a model of a twelve-DoF hand was created to perform contact analysis around a small set of cylinders dened by a single variable, diameter. Experiments were performed with the robot to validate and update the synergy-based models. Successful manipulation of a large range of cylindrical objects not previously introduced to the robot was demonstrated. This geometric synergy-based grasp planning method can be applied to any position-controlled humanoid hand to decrease the number of commanded DoF based on simple, measureable inputs in order to grasp commonly shaped objects. This method has the potential to vastly expand the library of objects the robot can manipulate.
\
}, keywords = {Dexterous Hand, Grasp, Humanoid, Manipulation, Synergy}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/farrell2017simply.pdf}, author = {Logan C. Farrell and Troy A. Dennis and Julia A. Badger and Marcia K. O{\textquoteright}Malley} } @proceedings {1890, title = {Toward training surgeons with motion-based feedback: Initial validation of smoothness as a measure of motor learning}, volume = {61}, number = {1}, year = {2017}, pages = {1531-1535}, abstract = {Surgery is a challenging domain for motor skill acquisition. A critical contributing factor in this difficulty is that feedback is often delayed from performance and qualitative in nature. Collection of highdensity motion information may offer a solution. Metrics derived from this motion capture, in particular indices of movement smoothness, have been shown to correlate with task outcomes in multiple domains, including endovascular surgery. The open question is whether providing feedback based on these metrics can be used to accelerate learning. In pursuit of that goal, we examined the relationship between a motion metric that is computationally simple to compute{\textemdash}spectral arc length{\textemdash}and performance on a simple but challenging motor task, mirror tracing. We were able to replicate previous results showing that movement smoothness measures are linked to overall performance, and now have performance thresholds to use in subsequent work on using these metrics for training.
}, doi = {10.1177/1541931213601747}, url = {https://doi.org/10.1177/1541931213601747}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/pandey2017hfes.pdf}, author = {Shivam Pandey and Michael D. Byrne and William H. Jantscher and Marcia K. O{\textquoteright}Malley and Priyanshu Agarwal} } @article {PMID:28944083, title = {White matter changes in corticospinal tract associated with improvement in arm and hand functions in incomplete cervical spinal cord injury: pilot case series}, journal = {Spinal Cord Series and Cases}, volume = {3}, year = {2017}, pages = {17028}, issn = {2058-6124}, doi = {10.1038/scsandc.2017.28}, url = {https://doi.org/10.1038/scsandc.2017.28}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Yozbatiran2017SpinalCordSeries.pdf}, author = {Yozbatiran, Nuray and Keser, Zafer and Hasan, Khader and Stampas, Argyrios and Korupolu, Radha and Kim, Sam and O{\textquoteright}Malley, Marcia K and Fregni, Felipe and Francisco, Gerard E} } @proceedings {1813, title = {A bio-inspired algorithm for identifying unknown kinematics from a discrete set of candidate models by using collision detection}, year = {2016}, pages = {418-423}, abstract = {Many robots are composed of interchangeable modular components, each of which can be independently controlled, and collectively can be disassembled and reassembled into new configurations. When assembling these modules into an open kinematic chain, there are some discrete choices dictated by the module geometry; for example, the order in which the modules are placed, the axis of rotation of each module with respect to the previous module, and/or the overall shape of the assembled robot. Although it might be straightforward for a human user to provide this information, there is also a practical benefit in the robot autonomously identifying these unknown, discrete forward kinematics. To date, a variety of techniques have been proposed to identify unknown kinematics; however, these methods cannot be directly applied during situations where we seek to identify the correct model amid a discrete set of options. In this paper, we introduce a method specifically for finding discrete robot kinematics, which relies on collision detection, and is inspired by the biological concepts of body schema and evolutionary algorithms. Under the proposed method, the robot maintains a population of possible models, stochastically identifies a motion which best distinguishes those models, and then performs that motion while checking for a collision. Models which correctly predicted whether a collision would occur produce candidate models for the next iteration. Using this algorithm during simulations with a Baxter robot, we were able to correctly determine the order of the links in 84\% of trials while exploring around 0.01\% of all possible models, and we were able to correctly determine the axes of rotation in 94\% of trials while exploring \< 0.1\% of all possible models.
}, isbn = {978-1-5090-3287-7}, issn = {978-1-5090-3287-7}, doi = {10.1109/BIOROB.2016.7523663}, url = {http://ieeexplore.ieee.org/abstract/document/7523663/}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/BioRob_2016_Algorithm.pdf}, author = {Dylan P. Losey and C. G. McDonald and Marcia K. O{\textquoteright}Malley} } @article {1777, title = {Design and optimization of an EEG-based brain machine interface (BMI) to an upper-limb exoskeleton for stroke survivors}, journal = {Frontiers in Neuroscience}, volume = {10}, year = {2016}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/FINS2016.pdf}, author = {Bhagat, N.A. and Venkatakrishnan, A. and Abibullaev, B. and Artz, E.J. and Yozbatiran, N. and Blank, A.A. and French, J. and Karmonik, C. and Grossman, R.G. and O{\textquoteright}Malley, M.K. and Francisco, G. and Contreras-Vidal, J.L.} } @article {1759, title = {Flexible robotics with electromagnetic tracking improve safety and efficiency during in vitro endovascular navigation}, journal = {Journal of Vascular Surgery}, volume = {63}, number = {1}, year = {2016}, pages = {285-286}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Schwein2016\%20-\%20Flexible\%20robotics\%20tracking.pdf}, author = {Adeline Schwein and Kramer, B.D. and Ponraj Chinnadurai and Sean Walker and O{\textquoteright}Malley, M.K. and Alan Lumsden and Jean Bismuth} } @proceedings {1822, title = {Improving the retention of motor skills after reward-based reinforcement by incorporating haptic guidance and error augmentation}, year = {2016}, pages = {857-863}, abstract = {There has been significant research aimed at leveraging programmable robotic devices to provide haptic assistance or augmentation to a human user so that new motor skills can be trained efficiently and retained long after training has concluded. The success of these approaches has been varied, and retention of skill is typically not significantly better for groups exposed to these controllers during training. These findings point to a need to incorporate a more complete understanding of human motor learning principles when designing haptic interactions with the trainee. Reward-based reinforcement has been studied for its role in improving retention of skills. Haptic guidance, which assists a user to complete a task, and error augmentation, which exaggerates error in order to enhance feedback to the user, have been shown to be beneficial for training depending on the task difficulty, subject ability, and task type. In this paper, we combine the presentation of reward-based reinforcement with these robotic controllers to evaluate their impact on retention of motor skill in a visual rotation task with tunable difficulty using either fixed or moving targets. We found that with the reward-based feedback paradigm, both haptic guidance and error augmentation led to better retention of the desired visuomotor offset during a simple task, while during a more complex task, only subjects trained with haptic guidance demonstrated performance superior to those trained without a controller.
}, isbn = {978-1-5090-3287-7}, issn = {978-1-5090-3287-7}, doi = {10.1109/BIOROB.2016.7523735}, url = {http://ieeexplore.ieee.org/abstract/document/7523735/}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Losey_BioRob_Improving.pdf}, author = {Dylan P. Losey and Laura H. Blumenschein and Marcia K. O{\textquoteright}Malley} } @article {1825, title = {Minimal assist-as-needed controller for upper limb robotic rehabilitation}, journal = {IEEE Transactions on Robotics}, volume = {32}, number = {1}, year = {2016}, month = {02/2016}, pages = {113-124}, chapter = {113}, abstract = {Robotic rehabilitation of the upper limb following neurological injury is most successful when subjects are engaged in the rehabilitation protocol. Developing assistive control strategies that maximize subject participation is accordingly an active area of research, with aims to promote neural plasticity and, in turn, increase the potential for recovery of motor coordination. Unfortunately, state-of-the-art control strategies either ignore more complex subject capabilities or assume underlying patterns govern subject behavior and may therefore intervene suboptimally. In this paper, we present a minimal assist-as-needed (mAAN) controller for upper limb rehabilitation robots. The controller employs sensorless force estimation to dynamically determine subject inputs without any underlying assumptions as to the nature of subject capabilities and computes a corresponding assistance torque with adjustable ultimate bounds on position error. Our adaptive input estimation scheme is shown to yield fast, stable, and accurate measurements regardless of subject interaction and exceeds the performance of current approaches that estimate only position-dependent force inputs from the user. Two additional algorithms are introduced in this paper to further promote active participation of subjects with varying degrees of impairment. First, a bound modification algorithm is described, which alters allowable error. Second, a decayed disturbance rejection algorithm is presented, which encourages subjects who are capable of leading the reference trajectory. The mAAN controller and accompanying algorithms are demonstrated experimentally with healthy subjects in the RiceWrist-S exoskeleton.
}, issn = {1552-3098}, doi = {10.1109/TRO.2015.2503726}, url = {http://ieeexplore.ieee.org/abstract/document/7360218/}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/TRO_2016.pdf}, author = {Ali Utku Pehlivan and Dylan P. Losey and Marcia K. O{\textquoteright}Malley} } @article {1784, title = {Modeling Electromechanical Aspects of Cyber-Physical Systems}, journal = {Journal of Software Engineering for Robotics (JOSER)}, volume = {7}, number = {1}, year = {2016}, month = {07/2016}, pages = {100-119}, chapter = {100}, abstract = {Model-based tools have the potential to significantly improve the process of developing novel cyber-physical systems (CPS). In this paper, we consider the question of what language features are needed to model such systems. We use a small, experimental hybrid systems modeling language to show how a number of basic and pervasive aspects of cyber-physical systems can be modeled concisely using the small set of language constructs. We then consider four, more complex, case studies from the domain of robotics. The first, a quadcopter, illustrates that these constructs can support the modeling of interesting systems. The second, a serial robot, provides a concrete example of why it is important to support static partial derivatives, namely, that it significantly improves the way models of rigid body dynamics can be expressed. The third, a linear solenoid actuator, illustrates the language{\textquoteright}s ability to integrate multiphysics subsystems. The fourth and final, a compass gait biped, shows how a hybrid system with non-trivial dynamics is modeled. Through this analysis, the work establishes a strong connection between the engineering needs of the CPS domain and the language features that can address these needs. The study builds the case for why modeling languages can be improved by integrating several features, most notably, partial derivatives, differentiation without duplication, and support for equations. These features do not appear to be addressed in a satisfactory manner in mainstream modeling and simulation tools.
}, keywords = {Cyber-Physical Systems, Domain-Specific Language}, issn = {2035-3928}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/102-585-1-PB.pdf}, author = {Yingfu Zeng and Rose, Chad G. and Walid Taha and Adam Duracz and Kevin Atkinson and Roland Philippsen and Robert Cartwright and Marcia O{\textquoteright}Malley} } @article {1768, title = {Smoothness of surgical tool tip motion correlates to skill in endovascular tasks}, journal = {IEEE Transactions on Human Machine Systems}, volume = {46}, number = {5}, year = {2016}, pages = {647-659}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/J23Estrada_press.pdf}, author = {Estrada, S. and Duran, C. and Schulz, D. and Bismuth, J. and Byrne, M.D. and O{\textquoteright}Malley, M.K.} } @proceedings {1826, title = {SOM and LVQ classification of endovascular surgeons using motion-based metrics}, year = {2016}, month = {01/2016}, pages = {227-237}, abstract = {An increase in the prevalence of endovascular surgery requires a growing number of proficient surgeons. Current endovascular surgeon evaluation techniques are subjective and time-consuming; as a result, there is a demand for an objective and automated evaluation procedure. Leveraging reliable movement metrics and tool-tip data acquisition, we here use neural network techniques such as LVQs and SOMs to identify the mapping between surgeons{\textquoteright} motion data and imposed rating scales. Using LVQs, only 50\ \% testing accuracy was achieved. SOM visualization of this inadequate generalization, however, highlights limitations of the present rating scale and sheds light upon the differences between traditional skill groupings and neural network clusters. In particular, our SOM clustering both exhibits more truthful segmentation and demonstrates which metrics are most indicative of surgeon ability, providing an outline for more rigorous evaluation strategies.
}, issn = {978-3-319-28517-7}, doi = {https://doi.org/10.1007/978-3-319-28518-4_20}, url = {https://link.springer.com/chapter/10.1007/978-3-319-28518-4_20}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/WSOM_2016.pdf}, author = {Kramer, B.D. and Dylan P. Losey and Marcia K. O{\textquoteright}Malley} } @article {1829, title = {A Time-Domain Approach To Control Of Series Elastic Actuators: Adaptive Torque And Passivity-Based Impedance Control}, journal = {IEEE/ASME Transactions on Mechatronics}, volume = {21}, number = {4}, year = {2016}, pages = {2085 - 2096}, abstract = {Robots are increasingly designed to physically interact with humans in unstructured environments, and as such must operate both accurately and safely. Leveraging compliant actuation, typically in the form of series elastic actuators (SEAs), can guarantee this required level of safety. To date, a number of frequency-domain techniques have been proposed which yield effective SEA torque and impedance control; however, these methods are accompanied by undesirable stability constraints. In this paper, we instead focus on a time-domain approach to the control of SEAs, and adapt two existing control techniques for SEA platforms. First, a model reference adaptive controller is developed, which requires no prior knowledge of system parameters and can specify desired closed-loop torque characteristics. Second, the time-domain passivity approach is modified to control desired impedances in a manner that temporarily allows the SEA to passively render impedances greater than the actuator{\textquoteright}s intrinsic stiffness. This approach also provides conditions for passivity when augmenting any stable SEA torque controller with an arbitrary impedance. The resultant techniques are experimentally validated on a custom prototype SEA.
}, issn = {1083-4435}, doi = {10.1109/TMECH.2016.2557727}, url = {http://ieeexplore.ieee.org/abstract/document/7457670/}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Losey_TMECH.pdf}, author = {Dylan P. Losey and Andrew Erwin and Craig G. McDonald and Fabrizio Sergi and Marcia K. O{\textquoteright}Malley} } @article {1787, title = {Transcranial direct current stimulation (tDCS) of the primary motor cortex and robot-assisted arm training in chronic incomplete cervical spinal cord injury: A proof of concept sham-randomized clinical study}, journal = {NeuroRehabilitation}, volume = {39}, year = {2016}, pages = {401{\textendash}411}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/TDCS_2016_Neurorehab.pdf}, author = {Nuray Yozbatirana and Zafer Keser and Matthew Davis and Argyrios Stampas and Marcia K. O{\textquoteright}Malley and Catherine Cooper-Hay and Joel Fronteraa and Felipe Fregni and Gerard E. Francisco} } @proceedings {1765, title = {Acumen: An open-source testbed for cyber-physical systems research}, year = {2015}, month = {10/2015}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/cyclone15Taha.pdf}, author = {Walid Taha and Adam Duracz and Yingfu Zeng and Kevin Atkinson and Ferenc A.Bartha and Paul Brauner and Jan Duracz and Fei Xu and Robert Cartwright and Michal Konecny and Eugenio Moggi and Jawad Masood and Pererik Andreasson and Jun Inoue and Anita Santanna and Roland Philippsen and Alexandre Chapoutot and O{\textquoteright}Malley, M.K. and Aaron Ames and Veronica Gaspes and Lise Hvatum and Shyam Mehta and Henrik Eriksson and Christian Grante} } @proceedings {1842, title = {Characterization of a hand-wrist exoskeleton, READAPT, via kinematic analysis of redundant pointing tasks}, year = {2015}, publisher = {IEEE}, address = {Singapore}, doi = { 10.1109/ICORR.2015.7281200}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/ICORR15_0190_MS_0.pdf}, author = {Rose, Chad G. and Sergi, Fabrizio and Yun, Youngmok and Madden, Kaci and Deshpande, Ashish D and O{\textquoteright}Malley, Marcia K} } @proceedings {1752, title = {Design of a parallel-group balanced controlled trial to test the effects of assist-as-needed robotic therapy}, year = {2015}, month = {08/2015}, address = {Singapore}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Sergi2015\%20-\%20Design\%20parallel\%20group\%20AAN\%20therapy.pdf}, author = {Sergi, F. and Pehlivan, A.U. and Fitle, K. and Nedley, K. and Yozbatiran, Nuray and Francisco,Gerard E. and O{\textquoteright}Malley, M.K.} } @proceedings {1756, title = {Development, control, and MRI-compatibility of the MR-SoftWrist}, year = {2015}, month = {08/2015}, pages = {187-192}, publisher = {IEEE}, address = {Singapore}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Erwin2015\%20-\%20MR\%20SoftWrist.pdf}, author = {Erwin,Andrew and O{\textquoteright}Malley, M.K. and Ress, D. and Fabrizio Sergi} } @article {1761, title = {An exploration of grip force regulation with a low-impedance myoelectric prosthesis featuring referred haptic feedback}, journal = {Journal of Neuroengineering and Rehabilitation}, volume = {12}, year = {2015}, doi = {10.1186/s12984-015-0098-1}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Brown2015\%20-\%20Grip\%20force\%20regulation.pdf}, author = {J.D. Brown and A. Paek and M. Syed and O{\textquoteright}Malley, M.K. and P.A. Shewokis and J.L. Contreras-Vidal and R.B. Gillespie and A.J. Davis} } @article {1760, title = {An index finger exoskeleton with series elastic actuation for rehabilitation: Design, control and performance characterization}, journal = {International Journal of Robotics Research}, volume = {34}, number = {14}, year = {2015}, pages = {1747-1772}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Agarwal2015\%20-\%20Index\%20finger\%20exo.pdf}, author = {Priyanshu Agarwal and Jonas Fox and Youngmok Yun and O{\textquoteright}Malley, M.K. and Ashish D. Deshpande} } @article {1723, title = {Interaction control capabilities of an MR-compatible compliant actuator for wrist sensorimotor protocols during fMRI}, journal = {IEEE/ASME Transactions on Mechatronics}, volume = {20}, number = {6}, year = {2015}, pages = {2678-2690}, abstract = {This paper describes the mechatronic design and characterization of a novel MR-compatible actuation system designed for a parallel force-feedback exoskeleton for measurement and/or assistance of wrist pointing movements during functional neuroimaging. The developed actuator is based on the interposition of custom compliant elements in series between a non-backdrivable MR-compatible ultrasonic piezoelectric motor and the actuator output. The inclusion of physical compliance allows estimation of interaction force, enabling force-feedback control and stable rendering of a wide range of haptic environments during continuous scanning. Through accurate inner-loop
velocity compensation and force-feedback control, the actuator is capable of displaying both a low-impedance, subject-in-charge mode, and a high stiffness mode. These modes enable the execution of shared haptic protocols during continuous fMRI.\
The detailed experimental characterization of the actuation system is presented, including a backdrivability analysis, demonstrating an achievable impedance range of 22 dB, within a bandwidth of 4 Hz (for low stiffness). The stiffness control bandwidth depends on the specific value of stiffness: a bandwidth of 4 Hz is achieved at low stiffness (10\% of the physical springs stiffness), while 8 Hz is demonstrated at higher stiffness. Moreover, coupled stability is demonstrated also for stiffness values substantially (25\%) higher than the physical stiffness of the spring. Finally, compatibility tests conducted in a 3T scanner are presented, validating the potential of inclusion of the actuator in an exoskeleton system for support of wrist movements during continuous MR scanning, without significant reduction in image quality.
}, keywords = {compliant actuators., Force control, functional MRI (fMRI), MR-compatible robotics}, doi = {10.1109/TMECH.2015.2389222}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/MR-compatible_actuator_v3.pdf}, author = {Fabrizio Sergi and Andrew Erwin and Marcia K. O{\textquoteright}Malley} } @article {1729, title = {Kinematics effectively delineate accomplished users of endovascular robotics with a physical training model}, journal = {Journal of Vascular Surgery}, volume = {61}, number = {2}, year = {2015}, pages = {535-541}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Duran_et_al_JVS2015.pdf}, author = {Cassidy Duran and Sean Estrada and Marcia O{\textquoteright}Malley and Alan B. Lumsden and Jean Bismuth} } @proceedings {1766, title = {Leveraging disturbance observer based torque control for improved impedance rendering with series elastic actuators}, year = {2015}, month = {09/2015}, pages = {1646-1651}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Mehling2015\%20-\%20Leveraging\%20DOB\%20SEAs.pdf}, author = {Mehling, J.S. and James Holley and O{\textquoteright}Malley, M.K.} } @article {1764, title = {A Method for Selecting Velocity Filter Cut-Off Frequency for Maximizing Impedance Width Performance in Haptic Interfaces}, journal = {ASME Journal of Dynamic Systems, Measurement, and Control }, volume = {137}, number = {2}, year = {2015}, doi = {10.1115/1.4028526}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Chawda2015\%20-\%20Selecting\%20cutoff\%20frequency.pdf}, author = {Chawda, Vinay and Ozkan Celik and O{\textquoteright}Malley, M.K.} } @article {1762, title = {The model for Fundamentals of Endovascular Surgery (FEVS) successfully defines the competent endovascular surgeon}, journal = {Journal of Vascular Surgery}, volume = {62}, number = {6}, year = {2015}, pages = {1660-1666}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/2015_JVS_Duran_press.pdf}, author = {Cassidy Duran and Sean Estrada and O{\textquoteright}Malley, M.K. and Malachi Sheahan and Murray Shames and Jason T Lee and Jean Bismuth} } @proceedings {1754, title = {Proportional sEMG based robotic assistance in an isolated wrist movement}, year = {2015}, month = {10/2015}, address = {Columbus, Ohio}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Atz2015\%20-\%20sEMG\%20based\%20robotic\%20assistance.pdf}, author = {Artz, E.J. and Blank, Amy A. and O{\textquoteright}Malley, M.K.} } @proceedings {1753, title = {A robotic exoskeleton for rehabilitation and assessment of the upper limb following incomplete spinal cord injury}, year = {2015}, month = {05/2015}, address = {Seattle, Washington}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Fitle2015\%20-\%20Robotic\%20exo\%20for\%20UL\%20rehab\%20after\%20iSCI.pdf}, author = {Fitle, K. and Pehlivan, A.U. and O{\textquoteright}Malley, M.K.} } @proceedings {1767, title = {The role of auxiliary and referred haptic feedback in myoelectric control}, year = {2015}, month = {06/2015}, pages = {13-18}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Treadway2015\%20-\%20Haptic\%20feedback\%20myoelectric\%20control.pdf}, author = {Treadway, Emma and Gillespie, B and Bolger, D. and Blank, A. and O{\textquoteright}Malley, M.K. and Davis, A.} } @article {1763, title = {On the stability and accuracy of high stiffness rendering in non-backdrivable actuators through series elasticity}, journal = {Mechatronics}, volume = {26}, year = {2015}, pages = {64-75}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Sergi2015\%20-\%20SEA\%20high\%20stiffness.pdf}, author = {Sergi, Fabrizio and O{\textquoteright}Malley, M.K.} } @article {6878466, title = {A Subject-Adaptive Controller for Wrist Robotic Rehabilitation}, journal = {Mechatronics, IEEE/ASME Transactions on}, volume = {20}, number = {3}, year = {2015}, pages = {1338 - 1350}, keywords = {adaptive control, Exoskeletons, Force, Iron, Medical treatment, nonlinear systems, parallel mechanisms, robot dynamics, robotic rehabilitation, Robots, Trajectory, Vectors, Wrist}, issn = {1083-4435}, doi = {10.1109/TMECH.2014.2340697}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/tmech-pehlivan-press.pdf}, author = {Pehlivan, A.U. and Sergi, F. and OMalley, M.K.} } @article {7080902, title = {Tactile Feedback of Object Slip Facilitates Virtual Object Manipulation}, journal = {Haptics, IEEE Transactions on}, volume = {PP}, number = {99}, year = {2015}, pages = {1-1}, keywords = {Force, force feedback, haptics, Phantoms, prosthetics, slip feedback, tactile sensors, vibrotactile feedback, Visualization}, issn = {1939-1412}, doi = {10.1109/TOH.2015.2420096}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/WalkerToH2015small.pdf}, author = {Walker, J. and Blank, A. and Shewokis, P. and O{\textquoteright}Malley, M.} } @proceedings {1712, title = {Compensating position drift in Time Domain Passivity Approach based teleoperation}, year = {2014}, month = {Feb}, doi = {10.1109/HAPTICS.2014.6775454}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/HS2014_PositionDrift_Chawda_Press.pdf}, author = {Chawda, Vinay and Ha Van Quang and O{\textquoteright}Malley, Marcia K. and Ryu, Jee-Hwan} } @proceedings {1743, title = {Compliant force-feedback actuation for accurate robot-mediated sensorimotor interaction protocols during fMRI}, year = {2014}, month = {08/2014}, publisher = {IEEE}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Sergi2014\%20-\%201DOF\%20MR\%20devices.pdf}, author = {Fabrizio Sergi and Andrew Erwin and Brian Cera and Marcia K. O{\textquoteright}Malley} } @article {1719, title = {Current Trends in Robot-Assisted Upper-Limb Stroke Rehabilitation: Promoting Patient Engagement in Therapy}, journal = {Current Physical Medicine and Rehabilitation Reports}, year = {2014}, doi = {10.1007/s40141-014-0056-z}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/2014_CPMRR_press.pdf}, author = {Amy A Blank and James A French and Ali Utku Pehlivan and Marcia K O{\textquoteright}Malley} } @proceedings {1713, title = {Design and characterization of a haptic paddle for dynamics education}, year = {2014}, month = {Feb}, doi = {10.1109/HAPTICS.2014.6775465}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/HS2014_HapticPaddle_Rose_Press.pdf}, author = {Rose, Chad G. and French, James A. and O{\textquoteright}Malley, Marcia K.} } @article {ROB:9438993, title = {Design and validation of the RiceWrist-S exoskeleton for robotic rehabilitation after incomplete spinal cord injury}, journal = {Robotica}, volume = {32}, year = {2014}, month = {12}, pages = {1415{\textendash}1431}, issn = {1469-8668}, doi = {10.1017/S0263574714001490}, url = {http://journals.cambridge.org/article_S0263574714001490}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/rob1400149_Press.pdf}, author = {Pehlivan,Ali Utku and Sergi,Fabrizio and Erwin,Andrew and Yozbatiran,Nuray and Francisco,Gerard E. and O{\textquoteright}Malley,Marcia K.} } @proceedings {1882, title = {Detecting movement intent from scalp EEG in a novel upper limb robotic rehabilitation system for stroke}, year = {2014}, month = {08/2014}, keywords = {Accuracy, Adult, bioelectric potentials, brain-computer interfaces, closed loop systems, closed-loop brain-machine interfaces, Computer-Assisted, diseases, electroencephalography, Electromyography, Exoskeletons, hemiparesis, Humans, Male, medical robotics, medical signal detection, medical signal processing, Middle Aged, Movement, movement intent detection, neurophysiology, Paresis, Patient rehabilitation, Robotics, Robots, scalp electroencephalography, Signal Processing, stroke, stroke rehabilitation, Support Vector Machine, Support vector machines, training, Upper Extremity, upper extremity dysfunction, upper limb robotic rehabilitation system, Young Adult}, doi = {10.1109/EMBC.2014.6944532}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/bhagat2014ieee.pdf}, author = {N. A. Bhagat and J. French and A. Venkatakrishnan and N. Yozbatiran and G. E. Francisco and M. K. O{\textquoteright}Malley and J. L. Contreras-Vidal} } @proceedings {1883, title = {On the development of objective metrics for surgical skills evaluation based on tool motion}, year = {2014}, publisher = {IEEE}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/estrada2014ieee.pdf}, author = {Estrada, Sean and O{\textquoteright}Malley, Marcia K and Duran, Cassidy and Schulz, Daryl and Bismuth, Jean} } @article {1695, title = {Identifying Successful Motor Task Completion via Motion-Based Performance Metrics}, journal = {Human-Machine Systems, IEEE Transactions on}, volume = {44}, year = {2014}, pages = {139-145}, keywords = {Accelerometers, human{\textendash}computer interaction, motion analysis}, doi = {10.1109/THMS.2013.2290129}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/O\%27Malley_et_al_IEEE_Trans_HMS_PRESS.pdf}, author = {O{\textquoteright}Malley, M.K. and Purkayastha, S.N. and Howie, N. and Byrne, M.D.} } @proceedings {1751, title = { A model matching framework for the synthesis of series elastic actuator impedance control}, year = {2014}, month = {06/2014}, pages = {249-254}, publisher = {IEEE}, address = {Palermo}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Mehling2014\%20-\%20Model\%20matching\%20framework\%20SEA.pdf}, author = {Mehling, J.S. and O{\textquoteright}Malley, M.K.} } @article {1718, title = {Position Synchronization in Bilateral Teleoperation Under Time-Varying Communication Delays}, year = {2014}, keywords = {adaptive control, Communication channels, Delay effects, delay systems, delays, Force, Force measurement, Ports (Computers), robust stability, Synchronization, telerobotics, time-varying systems}, doi = {10.1109/TMECH.2014.2317946}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/TMECH_Chawda2014_press.pdf}, author = {Chawda, V. and O{\textquoteright}Malley, M.K.} } @inbook {1701, title = {Robotics as a Tool for Training and Assessment of Surgical Skill}, booktitle = {Computational Surgery and Dual Training}, year = {2014}, pages = {365-375}, publisher = {Springer New York}, organization = {Springer New York}, keywords = {Assessment, Human{\^a}{\texteuro}{\textquotedblleft}robot interaction, Manual, Performance measures, Rehabilitation robotics, Robotics, Simulators, Skill, Skill training, Surgical, Tasks, Virtual reality}, isbn = {978-1-4614-8647-3}, doi = {10.1007/978-1-4614-8648-0_24}, url = {http://dx.doi.org/10.1007/978-1-4614-8648-0_24}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/CRISP_O\%27Malley_et_al_120611updated.pdf}, author = {O{\textquoteright}Malley, Marcia K. and Celik, Ozkan and Huegel, Joel C. and Byrne, Michael D. and Bismuth, Jean and Dunkin, Brian J. and Goh, Alvin C. and Miles, Brian J.}, editor = {Garbey, Marc and Bass, Barbara Lee and Berceli, Scott and Collet, Christophe and Cerveri, Pietro} } @proceedings {1721, title = {SYSTEM CHARACTERIZATION OF MAHI EXO-II: A ROBOTIC EXOSKELETON FOR UPPER EXTREMITY REHABILITATION}, year = {2014}, publisher = {ASME}, address = {San Antonio, TX}, abstract = {Neurological injuries, including stroke and spinal cord injury, typically result in significant motor impairments. These impairments negatively impact an individual{\textquoteright}s movement coordination, in turn affecting their ability to function independently. Intensively repetitous motion training has proven to restore some motor function after neurological injuries. This training is often labor-intensive and costly. By enabling therapists to train their patients intensively through consistent, repeatable movements, robotic rehabilitation systems offer a cost-effective solution requiring less labor and effort. The design of upper limb robotic therapy devices has been a topic of research for over two decades. Early devices were end-effector based, and guided the motion of a patient{\textquoteright}s hand to desired positions. Hardware and software designs emphasized the safety of the robotic devices, using control methods specifically designed to ensure safe interaction forces between the user and the device.
}, keywords = {5400:Research \& development, 9190:United States, Cost reduction, Engineering{\textendash}Mechanical Engineering, Medical research, Neurological disorders, Robotics, United States{\textendash}US}, isbn = {00256501}, url = {https://search.proquest.com/docview/1559578916?accountid=7064}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/sergi2014asmesmall.pdf}, author = {Sergi,Fabrizio and Blank,Amy and O{\textquoteright}Malley,Marcia} } @article {1694, title = {Vary Slow Motion: Effect of Task Forces on Movement Variability and Implications for a Novel Skill Augmentation Mechanism}, journal = {IEEE Robotics and Automation Magazine}, year = {2014}, month = {08/2014}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Celik-O\%27Malley_IEEE-RAM_2014_press.pdf}, author = {Ozkan Celik and Marcia K. O{\textquoteright}Malley} } @inbook {1700, title = {Workload and Performance Analyses with Haptic and Visually Guided Training in a Dynamic Motor Skill Task}, booktitle = {Computational Surgery and Dual Training}, year = {2014}, pages = {377-387}, publisher = {Springer New York}, organization = {Springer New York}, keywords = {force feedback, Haptics guidance, Joystick, Motor skill, performance, Skill acquisition, training, virtual environment, Workload}, isbn = {978-1-4614-8647-3}, doi = {10.1007/978-1-4614-8648-0_25}, url = {http://dx.doi.org/10.1007/978-1-4614-8648-0_25}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Huegel-NFVWTLX-CRISP.pdf}, author = {Huegel, Joel C. and O{\textquoteright}Malley, Marcia K.}, editor = {Garbey, Marc and Bass, Barbara Lee and Berceli, Scott and Collet, Christophe and Cerveri, Pietro} } @proceedings {1705, title = {Adaptive control of a serial-in-parallel robotic rehabilitation device}, year = {2013}, month = {June}, keywords = {absolute error performance, Adaptation models, adaptive control, closed form dynamic model, control system synthesis, Equations, Feedback, feedback gain, forearm rehabilitation, generalized coordinates, Manipulators, Mathematical model, medical robotics, model-based adaptive controller implementation, movement-based wrist, neurological injuries, Patient rehabilitation, RiceWrist, Robot kinematics, sensorimotor training, serial-in-parallel robot rehabilitation mechanism, serial-in-parallel robotic rehabilitation device, Trajectory, trajectory control, trajectory tracking performance, upper extremity robotic rehabilitation, Vectors}, doi = {10.1109/ICORR.2013.6650412}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Pehlivan_AAN_ICORR2013.pdf}, author = {Pehlivan, A.U. and Sergi, F. and O{\textquoteright}Malley, M.K.} } @proceedings {1650, title = {Design of a series elastic actuator for a compliant parallel wrist rehabilitation robot}, year = {2013}, month = {06/2013}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Sergi_SEA_paper_2.pdf}, author = {Fabrizio Sergi and Melissa M. Lee and Marcia K. O{\textquoteright}Malley} } @article {6197239, title = {Dynamic displacement sensing, system identification, and control of a speaker-based tendon vibrator via accelerometers}, journal = {Mechatronics, IEEE/ASME Transactions on}, volume = {18}, number = {2}, year = {2013}, pages = {812-817}, keywords = {Acceleration, Accelerometer-based displacement sensing, Accelerometers, Accuracy, artificial proprioception, differential accelerometers, displacement measurement, double integrator, feedforward, feedforward control, frequency domain system identification, high resolution optical encoder, kinesthetic illusions, parametric transfer function model, prosthetics, real-time dynamic displacement sensing, Sensors, speaker-based tendon vibrator control, tendon vibrator, Tendons, Transfer functions, vibration control, Vibrations}, issn = {1083-4435}, doi = {10.1109/TMECH.2012.2195326}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Celik_Gilbert_O\%27Malley_TMECH2013.pdf}, author = {Celik, O. and Gilbert, H.B. and O{\textquoteright}Malley, M.K.} } @article {1696, title = {Human-Scale Motion Capture with an Accelerometer-Based Gaming Controller}, journal = {Journal of Robotics and Mechatronics}, volume = {25}, number = {3}, year = {2013}, month = {03/2013}, pages = {458-465}, chapter = {458}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/JRM_PRESS_Purkayastha-et-al_2013.pdf}, author = {Purkayastha, Sagar N and Byrne, Michael D and O{\textquoteright}Malley, M.K.} } @proceedings {1703, title = {Interaction control for rehabilitation robotics via a low-cost force sensing handle}, year = {2013}, address = {Palo Alto, CA}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Erwin2013\%20-\%20RiceWrist-Grip.pdf}, author = {Andrew Erwin and Fabrizio Sergi and Vinay Chawda and Marcia K. O{\textquoteright}Malley} } @proceedings {1891, title = {Interaction control of a non-backdriveable MR-compatible actuator through series elasticity}, year = {2013}, publisher = {American Society of Mechanical Engineers}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/sergi2013asme.pdf}, author = {Sergi, Fabrizio and Chawda, Vinay and O{\textquoteright}Malley, Marcia K} } @proceedings {1702, title = {A Method for Selecting Velocity Filter Cutoff Frequency for Maximizing Impedance Width Performance in Haptic Interfaces}, year = {2013}, month = {10/2013}, address = {Palo Alto, CA}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Velocity\%20filtering_DSCC2013_final_version.pdf}, author = {Vinay Chawda and Ozkan Celik and Marcia K. O{\textquoteright}Malley} } @proceedings {1704, title = {Modeling Basic Aspects of Cyber-Physical Systems, Part II}, year = {2013}, address = {Tokyo, Japan}, abstract = {Achieving dexterous volitional control of an upper-limb prosthetic device will require multimodal sensory feedback that goes beyond vision. Haptic display is well-positioned to provide this additional sensory information. Haptic display, however, includes a diverse set of modalities that encode information differently. We have begun to make a comparison between two of these modalities, force feedback spanning the elbow, and amplitude-modulated vibrotactile feedback, based on performance in a functional grasp and lift task. In randomly ordered trials, we assessed the performance of N=11 participants (8 able-bodied, 3 amputee) attempting to grasp and lift an object using an EMG controlled gripper under three feedback conditions (no feedback, vibrotactile feedback, and force feed-back), and two object weights that were undetectable by vision. Preliminary results indicate differences between able-bodied and amputee participants in coordination of grasp and lift forces. In addition, both force feedback and vibrotactile feedback contribute to significantly better task performance (fewer slips) and better adaptation following an unpredicted weight change. This suggests that the development and utilization of internal models for predictive control is more intuitive in the presence of haptic feedback.
}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/WH2013_FINAL_PRESS_Brown_et_al.pdf}, author = {Jeremy D. Brown and Andrew Paek and Mashaal Syed and Marcia K. O{\textquoteright}Malley and Patricia Shewokis and Jose L. Contreras-Vidal and R. B. Gillespie} } @proceedings {1686, title = {Vibrotactile Feedback of Pose Error Enhances Myoelectric Control of a Prosthetic Hand}, year = {2013}, month = {04/2013}, pages = {531-536}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/WH2013_FINAL_PRESS_Christiansen_et_al.pdf}, author = {Ryan Christiansen and Jose Luis Contreras-Vidal and R B Gillespie and Patricia Shewokis and Marcia K. O{\textquoteright}Malley} } @proceedings {1471, title = {On the Correlation between Motion Data Captured from Low-Cost Gaming Controller and High Precision Encoders}, year = {2012}, month = {8/2012}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/EMBS2012_FINAL_Purkayastha.pdf}, author = {S.N. Purkayastha and M.D. Byrne and O{\textquoteright}Malley, M.K.} } @proceedings {1472, title = {Mechanical Design of RiceWrist-S: a Forearm-Wrist Exoskeleton for Stroke and Spinal Cord Injury Rehabilitation}, year = {2012}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/BIOROB_2012_Pehlivan_press.pdf}, author = {A.U. Pehlivan and S. Lee and O{\textquoteright}Malley, M.K.} } @article {1480, title = {Outcomes of Recent Efforts at Rice University to Incorporate Entrepreneurship Concepts into Interdisciplinary Capstone Design}, journal = {International Journal of Engineering Education}, volume = {28}, year = {2012}, pages = {1-5}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/oden2012ijee.pdf}, author = {Z.M. Oden and O{\textquoteright}Malley, M.K. and G. Woods and T. Kraft and B. Burke} } @proceedings {1473, title = {On the Performance of Passivity-based Control of Haptic Displays Employing Levant{\textquoteright}s Differentiator for Velocity Estimation}, year = {2012}, month = {03/2012}, pages = {415-419}, publisher = {IEEE}, address = {Vancouver, BC, Canada}, abstract = {In impedance-type haptic interfaces, encoders are typically employed to provide high resolution position measurements from which velocity is estimated, most commonly via the finite difference method (FDM). This velocity estimation technique performs reliably, unless very fast sampling is required, in which case noise or delay due to filtering of the position signals reduces accuracy in the estimate. Despite this limitation, FDM is attractive because it is a passive process, and therefore the passivity of the overall system can be guaranteed. Levant{\textquoteright}s differentiator is a viable alternative to FDM, and exhibits increased accuracy in velocity estimation at high sample rates compared to FDM. However, the passivity of this nonlinear velocity estimation technique cannot be shown using conventional methods. In this paper, we employ a time domain passivity framework to analyze and enforce passive behavior of Levant{\textquoteright}s differentiator for haptic displays in discrete time. The performance of this approach is explored both in simulation and experimentally on a custom made one degree-of-freedom haptic interface. Results demonstrate the effectiveness of the time domain passivity approach for compensating the active behavior observed with use of Levant{\textquoteright}s differentiator for velocity estimation.
}, isbn = {978-1-4673-0808-3}, doi = {10.1109/HAPTIC.2012.6183824}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/chawda.pdf}, author = {Vinay Chawda and Marcia K. O{\textquoteright}Malley} } @proceedings {1881, title = {Preliminary Results in Virtual Testing for Smart Buildings}, year = {2012}, publisher = {Springer Berlin Heidelberg}, address = {Berlin, Heidelberg}, abstract = {Smart buildings promise to revolutionize the way we live. Applications ranging from climate control to fire management can have significant impact on the quality and cost of these services. However, a smart building and any technology with direct effect on the safety of its occupants must undergo extensive testing. Virtual testing by means of computer simulation can significantly reduce the cost of testing and, as a result, accelerate the development of novel applications. Unfortunately, building physically-accurate simulation codes can be labor intensive.
}, isbn = {978-3-642-29154-8}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/bruneau2012lnicst.pdf}, author = {Bruneau, Julien and Consel, Charles and O{\textquoteright}Malley, Marcia and Taha, Walid and Hannourah, Wail Masry}, editor = {S{\'e}nac, Patrick and Ott, Max and Seneviratne, Aruna} } @article {1563, title = {The RiceWrist Grip: A Means to Measure Grip Strength of Patients Using the RiceWrist}, year = {2012}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/grip_sensor_poster_mission_connect_0.pdf}, author = {Ryan Quincy and Andrew Erwin and A.U. Pehlivan and Yozbatiran, Nuray and Gerard Francisco and Marcia K. O{\textquoteright}Malley} } @article {1468, title = {RiceWrist Robotic Device for Upper Limb Training: Feasibility Study and Case Report of Two Tetraplegic Persons with Spinal Cord Injury}, journal = {International Journal of Biological Engineering}, volume = {2}, number = {4}, year = {2012}, pages = {27-38}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/IntlJBiologicalEngineering_2012_Kadivar.pdf}, author = {Z. Kadivar and J.L. Sullivan and D.P. Eng and A.U. Pehlivan and O{\textquoteright}Malley, M.K. and N. Yozbatiran and G.E. Francisco} } @article {1698, title = {Robotic training and clinical assessment of upper extremity movements after spinal cord injury; a single case report}, journal = {Journal of Rehabilitation Medicine}, volume = {44}, year = {2012}, month = {01/2012}, pages = {186-188}, chapter = {186}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/J_Rehab_Medicine_2012_Final_press_version.pdf}, author = {Yozbatiran, Nuray and Berliner, J. and O{\textquoteright}Malley, M.K. and Pehlivan, A.U. and Z. Kadivar and Boake, Corwin and Gerard E. Francisco} } @article {powell_task, title = {The Task-Dependent Efficacy of Shared-Control Haptic Guidance Paradigms}, journal = {{IEEE} Transactions on Haptics}, volume = {5}, number = {3}, year = {2012}, pages = {208 {\textendash}219}, abstract = {Shared-control haptic guidance is a common form of robot-mediated training used to teach novice subjects to perform dynamic tasks. Shared-control guidance is distinct from more traditional guidance controllers, such as virtual fixtures, in that it provides novices with real-time visual and haptic feedback from a real or virtual expert. Previous studies have shown varying levels of training efficacy using shared-control guidance paradigms; it is hypothesized that these mixed results are due to interactions between specific guidance implementations ( {amp;\#x201C;paradigms} {amp;\#x201D;)} and tasks. This work proposes a novel guidance paradigm taxonomy intended to help classify and compare the multitude of implementations in the literature, as well as a revised proxy rendering model to allow for the implementation of more complex guidance paradigms. The efficacies of four common paradigms are compared in a controlled study with 50 healthy subjects and two dynamic tasks. The results show that guidance paradigms must be matched to a task{\textquoteright}s dynamic characteristics to elicit effective training and low workload. Based on these results, we provide suggestions for the future development of improved haptic guidance paradigms.
}, issn = {1939-1412}, doi = {10.1109/TOH.2012.40}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/J8Powell2012.pdf}, author = {Powell, Dane and Marcia K. O{\textquoteright}Malley} } @proceedings {1114, title = {Application of Levant{\textquoteright}s Differentiator for Velocity Estimation and Increased Z-Width in Haptic Interfaces}, year = {2011}, month = {06/2011}, pages = {403-408}, publisher = {IEEE}, address = {Istanbul, Turkey}, issn = {978-1-4577-0297-6}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/1114-chawda.pdf}, author = {Vinay Chawda and Ozkan Celik and Marcia K. O{\textquoteright}Malley} } @proceedings {1295, title = {Comparison of Reaching Kinematics During Mirror and Parallel Robot Assisted Movements}, year = {2011}, month = {02/2011}, address = {Newport Beach, CA}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/1295-MMVR18-Kadivar_Z.pdf}, author = {Zahra KADIVAR and Cynthia SUNG and Zachary THOMPSON and Marcia O{\textquoteright}MALLEY and Michael LIEBSCHNER and Deng, Zhigang} } @proceedings {1478, title = {Design of a low-cost series elastic actuator for multi-robot manipulation}, year = {2011}, month = {may}, doi = {10.1109/ICRA.2011.5980534}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/campbell2011ieee.pdf}, author = {Campbell, E. and Kong, Z.C. and Hered, W. and Lynch, A.J. and O{\textquoteright}Malley, M.K. and McLurkin, J.} } @proceedings {1476, title = {Effect of Progressive Visual Error Amplification on Human Motor Adaptation}, year = {2011}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/ICORR11_Sung-O\%27Malley-PRESS.pdf}, author = {C. Sung and O{\textquoteright}Malley, M.K.} } @proceedings {1049, title = {Efficacy of Shared-Control Guidance Paradigms for Robot-Mediated Training}, year = {2011}, address = {Istanbul, Turkey}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/1049-HAP11_0064_FI.pdf}, author = {Powell, Dane and O{\textquoteright}Malley, M.K.} } @proceedings {chawda2011, title = {A Lyapunov Approach for SOSM Based Velocity Estimation and its Application to Improve Bilateral Teleoperation Performance}, year = {2011}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/1322-DSCC2011-6181.pdf}, author = {Vinay Chawda and Marcia K. O{\textquoteright}Malley} } @proceedings {1879, title = {Mechanical design of a distal arm exoskeleton for stroke and spinal cord injury rehabilitation}, year = {2011}, pages = {633-637}, publisher = {IEEE}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/pehlivan2011ieee.pdf}, author = {Pehlivan, Ali Utku and Celik, Ozkan and O{\textquoteright}Malley, Marcia K} } @proceedings {1475, title = {Motor Skill Acquisition in a Virtual Gaming Environment}, year = {2011}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/howie2011hfes.pdf}, author = {N. Howie and S.N. Purkayastha and M.D. Byrne and O{\textquoteright}Malley, M.K.} } @proceedings {1474, title = {A Neuromuscular Elbow Model for Analysis of Force and Movement Variability in Slow Movements}, year = {2011}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/celik2011ieee.pdf}, author = {O. Celik and O{\textquoteright}Malley, M.K.} } @proceedings {1477, title = {Rate of human motor adaptation under varying system dynamics}, year = {2011}, month = {june}, doi = {10.1109/WHC.2011.5945480}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/ahmetcan2011haptics.pdf}, author = {Erdogan, A. and Israr, A. and O{\textquoteright}Malley, M.K. and Patoglu, V.} } @proceedings {1880, title = {Robotic training and clinical assessment of forearm and wrist movements after incomplete spinal cord injury: A case study}, year = {2011}, month = {June}, pages = {619-622}, abstract = {The effectiveness of a robotic training device was evaluated in a 24-year-old male, cervical level four, ASIA Impairment Scale D injury. Robotic training of both upper extremities was provided for three hr/day for ten consecutive sessions using the RiceWrist, an electrically-actuated forearm and wrist haptic exoskeleton device that has been designed for rehabilitation applications. Training involved wrist flexion/extension, radial/ulnar deviation and forearm supination/pronation. Therapy sessions were tailored, based on the patient{\textquoteright}s movement capabilities for the wrist and forearm, progressed gradually by increasing number of repetitions and resistance. Outcome measures included the ASIA upper-extremity motor score, grip and pinch strength, the Jebsen-Taylor Hand Function test and the Functional Independence Measure. After the training, improvements were observed in pinch strength, and functional tasks. The data from one subject provides valuable information on the feasibility and effectiveness of robotic-assisted training of forearm and hand functions after incomplete spinal cord injury.
}, keywords = {age 24 yr, arm motor function recovery, ASIA upper-extremity motor score, biomechanics, clinical assessment, electrically-actuated forearm, Forearm, forearm movement, forearm pronation, forearm supination, functional independence measure, functional tasks, grip, Haptic interfaces, Humans, injuries, Jebsen-Taylor hand function test, Joints, Male, medical robotics, Medical treatment, Muscles, neurophysiology, patient movement capabilities, Patient rehabilitation, Patient treatment, pinch strength, radial-ulnar deviation, rehabilitation applications, robotic training, Robots, Spinal Cord Injuries, spinal cord injury, training, Wrist, wrist extension, wrist flexion, wrist haptic exoskeleton device, wrist movement, Young Adult}, doi = {10.1109/ICORR.2011.5975425}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/yozbatiran2011ieee.pdf}, author = {N. Yozbatiran and J. Berliner and C. Boake and M. K. O{\textquoteright}Malley and Z. Kadivar and G. E. Francisco} } @proceedings {1293, title = {Robotic Training and Kinematic Analysis of Arm and Hand after Incomplete Spinal Cord Injury: A Case Study.}, year = {2011}, month = {06/2011}, address = {Zurich Switzerland}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/1293-PID1757607\%5B1\%5D.pdf}, author = {Z. Kadivar and J.L. Sullivan and D.P. Eng and A.U. Pehlivan and M.K. O{\textquoteright}Malley and N. Yozbatiran and G.E.Francisco} } @proceedings {1294, title = {Spatial and Temporal Movement Characteristics after Robotic Training of Arm and Hand: A Case Study of a Person with Incomplete Spinal Cord Injury}, year = {2011}, month = {09/2011}, address = {San Francisco, CA}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/1294-IROS\%202011\%20Eng\%20Kadivar.pdf}, author = {D.P. Eng and Z. Kadivar and J.L. Sullivan and A.U. Pehlivan and M.K. O{\textquoteright}Malley and G.E. Francisco and N.Yozbatiran} } @inbook {1868, title = {Surgical Robotics: Innovations, Development, and Shortcomings}, booktitle = {Pumps and Pipes}, year = {2011}, pages = {33-44}, publisher = {Springer US}, organization = {Springer US}, address = {Boston, MA}, abstract = {Robotic devices have been used in the industrial field for over 40 years, while their introduction has been slower into the medical field with many requirements driven by the nature of human tissue and safety. These surgical assistance systems provide intelligent, versatile tools that augment a physician{\textquoteright}s ability to treat patients. Steerable robotic catheters may overcome many of the limitations of standard catheter technology, enhance target vessel cannulation, and reduce instrumentation, while improving overall physician performance. External robotics allows access to a body cavity through percutaneous ports with a high precision, high magnification manipulation of tissue. Robotics-driven imaging systems enhance dynamic data acquisition and provide high speed integration, facilitating image-guided navigation and augmenting other robotic systems. A lack of haptics remains a significant safety issue.
}, isbn = {978-1-4419-6012-2}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Bismuth2011pumpspipes.pdf}, author = {Bismuth, Jean and O{\textquoteright}Malley, Marcia K.}, editor = {Davies, Mark G. and Lumsden, Alan B. and Kline, William E. and Kakadiaris, Ioannis} } @article {1079, title = {Vision-Based Force Sensing for Nanomanipulation}, journal = {IEEE /ASME Transactions on Mechatronics}, year = {2011}, type = {Journal Article}, abstract = {A vision-based algorithm for estimating tip interaction forces on a deflected Atomic Force Microscope (AFM) cantilever is described. Specifically, we propose that the algorithm can estimate forces acting on an Atomic Force Microscope (AFM) cantilever being used as a nanomanipulator inside a Scanning Electron Microscope (SEM). The vision based force sensor can provide force feedback in real-time, a feature absent in many SEMs. A methodology based on cantilever slope detection is used to estimate the forces acting on the cantilever tip. The technique was tested on a scaled model of the nanoscale AFM cantilever and verified using theoretical estimates as well as direct strain measurements. Artificial SEM noise was introduced in the macroscale images to characterize our sensor under varying levels of noise and other SEM effects. Prior knowledge about the cantilever is not required, and the algorithm runs independent of human input. The method is shown to be effective under varying noise levels, and demonstrates improving performance as magnification levels are decreased. Therefore, we conclude that the vision-based force sensing algorithm is best suited for continuous operation of the SEM, fast scanning rates, and large fields-of-view associated with low magnification levels.}, issn = {1083-4435 }, doi = {10.1109/TMECH.2010.2093535}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5692832}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/1079-05692832.pdf}, author = {Vinay Chawda and O{\textquoteright}Malley, M.K.} } @proceedings {1878, title = {Work in progress{\textemdash}Implementing and evaluating efforts to engage interdisciplinary teams to solve real-world design challenges}, year = {2011}, publisher = {IEEE}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/oden2011fie.pdf}, author = {Oden, Z Maria and O{\textquoteright}Malley, Marcia K and Woods, Gary L and Volz, Tracy M} } @proceedings {899, title = {Analysis and comparison of low cost gaming controllers for motion analysis}, year = {2010}, month = {07/2010}, address = {Montreal, Canada}, abstract = {Gaming controllers are attractive devices for research due to their onboard sensing capabilities and low cost. However, a proper quantitative analysis regarding their suitability for motion capture has yet to be conducted. In this paper, a detailed analysis of the sensors of two of these controllers, the Nintendo Wiimote and the Sony Playstation 3 Sixaxis is presented. The acceleration data from the sensors were plotted and compared with computed acceleration data derived from a high resolution encoder, then correlated to determine the performance of the gaming controllers. The results show high correlation between the acceleration data of the sensors and the computed acceleration, and more consistency in the sensors of the Sixaxis. The applications of the findings are discussed with respect to potential research ventures.
}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/899-AIM\%20final\%20conference\%20version.pdf}, author = {Purkayastha, Sagar N and Eckenstein, Nick and Byrne, Michael D and O{\textquoteright}Malley, M.K.} } @proceedings {773, title = {Co-presentation of Force Cues for Skill Transfer via Shared-control Systems}, year = {2010}, abstract = {During training and rehabilitation with haptic devices, it is often necessary to simultaneously present force cues arising from different haptic models (such as guidance cues and environmental forces). Multiple force cues are typically summed to produce a single output force, which conveys only relative information about the original force cues and may not be useful to trainees. Two force copresentation paradigms are proposed as potential solutions to this problem: temporal separation of force cues, where one type of force is overlaid with the other in staggered pulses, and spatial separation, where the forces are presented via multiple haptic devices. A generalized model for separating task and guidance forces in a virtual environment is also proposed. In a pilot study where sixteen participants were trained in a dynamic target-hitting task using these co-presentation paradigms, simple summation was in fact most effective at eliciting skill transfer in most respects. Spatial separation imposed the lowest overall workload on participants, however, and might thus be more appropriate than summation in tasks with other significant physical or mental demands. Temporal separation was relatively inferior at eliciting skill transfer, but it is hypothesized that this paradigm would have performed considerably better in a non-rhythmic task, and the need for further research is indicated.
}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/773-Submission.pdf}, author = {Powell, Dane and O{\textquoteright}Malley, M.K.} } @proceedings {5444681, title = {Discrimination of consonant articulation location by tactile stimulation of the forearm}, year = {2010}, month = {25-26}, pages = {47 -54}, keywords = {consonant articulation location, dorsal forearm skin, Haptic interfaces, localized vibrations map, psychology, speech, speech processing, spoken consonants, tactile cues, tactile sensors, tactile stimulation, touch (physiological)}, doi = {10.1109/HAPTIC.2010.5444681}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/HS10_Wong-Israr-O\%27Malley.pdf}, author = {Wong, E.Y. and Ali Israr and O{\textquoteright}Malley, M.K.} } @article {1699, title = {Disturbance observer-based force estimation for haptic feedback}, journal = {ASME Journal of Dynamic Systems, Measurement and Control}, volume = {133}, year = {2010}, month = {12/2010}, pages = {014505-1--014505-4}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Gupta_O\%27Malley_2011_JDSMC_dist_obs_PRESS.pdf}, author = {Abhishek Gupta and Marcia K. O{\textquoteright}Malley} } @proceedings {1875, title = {A Fully Automated System for the Preparation of Samples for Cryo-Electron Microscopy}, year = {2010}, publisher = {American Society of Mechanical Engineers}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/thompson2010asme.pdf}, author = {Thompson, Zachary J and Johnson, Kevin L and Overby, Nicolas and Chidi, Jessica I and Pryor, William K and O{\textquoteright}Malley, Marcia K} } @article {917, title = {Incorporating simulation in vascular surgery education}, journal = {Journal of vascular surgery : official publication, the Society for Vascular Surgery [and] International Society for Cardiovascular Surgery, North American Chapter}, year = {2010}, month = {2010/08/05}, pages = { - }, publisher = {Mosby-Year Book}, isbn = {0741-5214}, url = {http://linkinghub.elsevier.com/retrieve/pii/S0741521410013054?showall=true}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/bismuth2010jvascsurg.pdf}, author = {Jean Bismuth and Michael A. Donovan and O{\textquoteright}Malley, M.K. and Hosam F. El Sayed and Joseph J. Naoum and Eric K. Peden and Mark G. Davies and Alan B. Lumsden} } @proceedings {912, title = {Long-term double integration of acceleration for position sensing and frequency domain system identification}, year = {2010}, address = {Montr{\'e}al, Canada}, abstract = {We present results from successful implementation of long-term (\>10 seconds) real-time integration of acceleration to measure position. We evaluated two analog circuit designs for double integration of an acceleration signal. Our circuit design features three high-pass filters and two first order integrators, leading to a critically damped double integrator. The second design we have implemented is a second order underdamped integrator reported in the literature. Accuracy of both circuits in sensing position based on only accelerometer readings was experimentally evaluated by comparison with encoder readings. We conclude that a critically damped double integrator coupled with an accelerometer is well-suited for frequency domain system identification, thanks to reliable position measurement capability with minimal interference to system dynamics.
}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/912-Gilbert2010AIM.pdf}, author = {Gilbert, Hunter B and Ozkan Celik and O{\textquoteright}Malley, M.K.} } @proceedings {mathequations, title = {Mathematical Equations as Executable Models of Mechanical Systems}, year = {2010}, abstract = {Cyber-physical systems comprise digital components that directly interact with a physical environment. Specifying the behavior desired of such systems requires analytical modeling of physical phenomena. Similarly, testing them requires simulation of continuous systems. While numerous tools support later stages of developing simulation codes, there is still a large gap between analytical modeling and building running simulators. This gap significantly impedes the ability of scientists and engineers to develop novel cyber-physical systems. We propose bridging this gap by automating the mapping from analytical models to simulation codes. Focusing on mechanical systems as an important class of models of physical systems, we study the form of analytical models that arise in this domain, along with the process by which domain experts map them to executable codes. We show that the key steps needed to automate this mapping are 1) a light-weight analysis to partially direct equations, 2) a binding-time analysis, and 3) an efficient implementation of symbolic differentiation. As such, our work pinpoints and highlights a number of limitations in the state of the art in tool support of simulation, and shows how some of these limitations can be overcome.
}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/zhu2010ieee.pdf}, author = {Angela Yun Zhu and Edwin Westbrook and Jun Inoue and Alexandre Chapoutot and Cherif Salama and Marisa Peralta and Travis Martin and Walid Taha and Robert Cartwright and O{\textquoteright}Malley, M.K.} } @article {911, title = {Normalized movement quality measures for therapeutic robots strongly correlate with clinical motor impairment measures}, journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering}, volume = {18}, number = {4}, year = {2010}, pages = {433-444}, abstract = {In this paper, we analyze the correlations between four clinical measures (Fugl{\textendash}Meyer upper extremity scale, Motor Activity Log, Action Research Arm Test, and Jebsen-Taylor Hand Function Test) and four robotic measures (smoothness of movement, trajectory error, average number of target hits per minute, and mean tangential speed), used to assess motor recovery. Data were gathered as part of a hybrid robotic and traditional upper extremity rehabilitation program for nine stroke patients. Smoothness of movement and trajectory error, temporally and spatially normalized measures of movement quality defined for point-to-point movements, were found to have significant moderate to strong correlations with all four of the clinical measures. The strong correlations suggest that smoothness of movement and trajectory error may be used to compare outcomes of different rehabilitation protocols and devices effectively, provide improved resolution for tracking patient progress compared to only pre- and post-treatment measurements, enable accurate adaptation of therapy based on patient progress, and deliver immediate and useful feedback to the patient and therapist.}, url = {http://dx.doi.org/10.1109/TNSRE.2010.2047600}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/911-Celik2010TNSRE.pdf}, author = {Ozkan Celik and O{\textquoteright}Malley, M.K. and Boake, Corwin and H.S. Levin and Yozbatiran, Nuray and Reistetter, Timothy} } @proceedings {1877, title = {A Preliminary ACT-R model of a continuous motor task}, year = {2010}, publisher = {SAGE Publications Sage CA: Los Angeles, CA}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/byme2010hfes.pdf}, author = {Byrne, Michael D and O{\textquoteright}Malley, Marcia K and Gallagher, Melissa A and Purkayastha, Sagar N and Howie, Nicole and Huegel, Joel C} } @proceedings {1746, title = {Progressive haptic and visual guidance for training in a virtual dynamic task}, year = {2010}, month = {March}, keywords = {Design engineering, dynamic motor skill, Error correction, expertise-based performance measures, Feedback, Fixtures, Haptic interfaces, haptic virtual environment, input frequency, Mechatronics, Performance analysis, progressive guidance controller, progressive haptic guidance, progressive visual guidance, Protocols, Rehabilitation robotics, skill component measures, target-hitting task, training protocol, trajectory error, virtual dynamic task, virtual environment, Virtual reality, visual guidance scheme}, doi = {10.1109/HAPTIC.2010.5444632}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Huegel2010HS.pdf}, author = {Huegel, J.C. and O{\textquoteright}Malley, M.K.} } @proceedings {1876, title = {Toward improved sensorimotor integration and learning using upper-limb prosthetic devices}, year = {2010}, pages = {5077-5080}, publisher = {IEEE}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Gillespie2010ieee.pdf}, author = {Gillespie, R Brent and Contreras-Vidal, Jose Luis and Shewokis, Patricia A and O{\textquoteright}Malley, Marcia K and Brown, Jeremy D and Agashe, Harshavardhan and Gentili, Rodolphe and Davis, Alicia} } @proceedings {111, title = {Compact and low-cost tendon vibrator for inducing proprioceptive illusions}, year = {2009}, month = {03/2009}, publisher = {IEEE}, address = {Salt Lake City, Utah}, abstract = {Recent literature suggests that inducing proprioceptive movement illusions with predefined movement trajectories via tendon vibration requires use of multiple vibrators and precisely controlled frequency profiles. In this study, we report the design, modeling and control of a compact, low-cost tendon vibrator and illustrate its capability of accurately following time-varying frequency profiles. During the demonstration, participants will test the vibrator to experience illusory elbow flexion.
}, keywords = {artificial proprioception, proprioceptive illusions, tendon vibration}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/111-Celik2009WHC.pdf}, author = {Ozkan Celik and O{\textquoteright}Malley, M.K. and Brent Gillespie and Shewokis, Patricia A. and Contreras-Vidal, Jose Luis} } @proceedings {290, title = {Designing and Implementation of a Tactile Respiratory Management System}, year = {2009}, month = {03/2009}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/290-HSEMB_Abstract_final.pdf}, author = {Dillon P. Eng and Ali Israr and O{\textquoteright}Malley, M.K.} } @proceedings {526, title = {Effects of Force and Displacement Cues while Adapting in a Rhythmic Motor Task}, year = {2009}, pages = {32-33}, address = {Seattle, WA}, abstract = {\
This paper explores the effects of magnitude and phase cues on human motor adaptation. Participants were asked to excite virtual second-order systems at their resonance frequencies via a two-degree of freedom haptic interface, with visual and visual plus haptic feedback conditions. Their motor adaptations were studied through catch trials. The results indicate that, i) humans adapt to a nominal virtual system resonant frequency, ii) humans shift to higher and lower natural frequencies during catch trials regardless of feedback modality and force cues, iii) humans can detect changes in natural frequency when gain, magnitude, and phase cues are manipulated independently, and iv) humans are able to detect changes in natural frequency when the feedback (visual or visual plus haptic) is delayed such that the phase shift between the nominal system and catch trial system is zero.
\
}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/israr2009robotics.pdf}, author = {Ali Israr and Hakan Kapson and Volkan Patoglu and O{\textquoteright}Malley, M.K.} } @proceedings {107, title = {Effects of Magnitude and Phase Cues on Human Motor Adaptation}, year = {2009}, month = {03/2009}, pages = {344-349}, publisher = {IEEE}, address = {Salt Lake city, Utah}, abstract = {Recent findings have shown that humans can adapt their internal control model to account for the changing dynamics of systems they manipulate. In this paper, we explore the effects of magnitude and phase cues on human motor adaptation. In our experiments, participants excite virtual second-order systems at resonance via a two-degree of freedom haptic interface, with visual and visual plus haptic feedback conditions. Then, we change the virtual system parameters and observe the resulting motor adaptation in catch trials. Through four experimental conditions we demonstrate the effects of magnitude and phase cues on human motor adaptation. First, we show that humans adapt to a nominal virtual system resonant frequency. Second, humans shift to higher and lower natural frequencies during catch trials regardless of feedback modality and force cues. Third, participants can detect changes in natural frequency when gain, magnitude, and phase cues are manipulated independently. Fourth, participants are able to detect changes in natural frequency when the feedback (visual or visual plus haptic) is delayed such that the phase shift between the nominal system and catch trial system is zero. The persistent ability of participants to perform system identification of the dynamic systems which they control, regardless of the cue that is conveyed, demonstrates the human{\textquoteright}s versatility with regard to manual control situations. We intend to further investigate human motor adaptation and the time for adaptation in order to improve the efficacy of shared control methodologies for training and rehabilitation in haptic virtual environments.
}, keywords = {catch trials, internal models, motor adaptation, Rhythmic motion}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/107-0156.pdf}, author = {Ali Israr and Hakan Kapson and Volkan Patoglu and O{\textquoteright}Malley, M.K.} } @proceedings {1871, title = {On the efficacy of haptic guidance schemes for human motor learning}, year = {2009}, pages = {203-206}, publisher = {Springer}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Patoglu2009iupesm.pdf}, author = {Patoglu, Volkan and Li, Yvonne and O{\textquoteright}Malley, Marcia K} } @article {856, title = {Expertise-Based Performance Measures in a Virtual Training Environment}, journal = {Presence}, volume = {18}, year = {2009}, note = {doi: 10.1162/pres.18.6.449}, month = {2009/12/01}, pages = {449 - 467}, publisher = {MIT Press}, abstract = {This paper introduces and validates quantitative performance measures for a rhythmic target-hitting task. These performance measures are derived from a detailed analysis of human performance during a month-long training experiment where participants learned to operate a 2-DOF haptic interface in a virtual environment to execute a manual control task. The motivation for the analysis presented in this paper is to determine measures of participant performance that capture the key skills of the task. This analysis of performance indicates that two quantitative measures{\textemdash}trajectory error and input frequency{\textemdash}capture the key skills of the target-hitting task, as the results show a strong correlation between the performance measures and the task objective of maximizing target hits. The performance trends were further explored by grouping the participants based on expertise and examining trends during training in terms of these measures. In future work, these measures will be used as inputs to a haptic guidance scheme that adjusts its control gains based on a real-time assessment of human performance of the task. Such guidance schemes will be incorporated into virtual training environments for humans to develop manual skills for domains such as surgery, physical therapy, and sports.
}, isbn = {1054-7460}, url = {http://dx.doi.org/10.1162/pres.18.6.449}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/856-Huegel2009Presence.pdf}, author = {Joel C. Huegel and Ozkan Celik and Ali Israr and O{\textquoteright}Malley, M.K.} } @proceedings {1873, title = {Functionally biarticular control for smart prosthetics}, year = {2009}, pages = {627-628}, publisher = {IEEE}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/gillespie2009IEEE.pdf}, author = {Gillespie, Brent and Baker, John and O{\textquoteright}Malley, Marcia and Shewokis, Patricia and Contreras-Vidal, Jose Luis} } @proceedings {529, title = {Impact of visual error augmentation methods on task performance and motor adaptation}, year = {2009}, pages = {793-798}, abstract = {We hypothesized that augmenting the visual error feedback provided to subjects training in a point-to-point reaching task under visual distortion would improve the amount and speed of adaptation. Previous studies showing that human learning is error-driven and that visual error augmentation can improve the rate at which subjects decrease their trajectory error in such a task provided the motivation for our study. In a controlled experiment, subjects were required to perform point-to- point reaching movements in the presence of a rotational visual distortion. The amount and speed of their adaptation to this distortion were calculated based on two performance measures: trajectory error and hit time. We tested how three methods of error augmentation (error amplification, traditional error offsetting, and progressive error offsetting) affected the amount and speed of adaptation, and additionally propose definitions for {\textquotedblleft}amount{\textquotedblright} and {\textquotedblleft}speed{\textquotedblright} of adaptation in an absolute sense that are more practical than definitions used in previous studies. It is concluded that traditional error offsetting promotes the fastest learning, while error amplification promotes the most complete learning. Progressive error offsetting, a novel method, resulted in slower training than the control group, but we hypothesize that it could be improved with further tuning and indicate a need for further study of this method. These results have implications for improvement in motor skill learning across many fields, including rehabilitation after stroke, surgical training, and teleoperation.
}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/529-Celik2009ICORRpublished.pdf}, author = {Ozkan Celik and Powell, Dane and O{\textquoteright}Malley, M.K.} } @proceedings {920, title = {Implementing Haptic Feedback Environments from High-level Descriptions}, year = {2009}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/zhu2009shoes.pdf}, author = {Angela Yun Zhu and Jun Inoue and Marisa Peralta and Walid Taha and O{\textquoteright}Malley, M.K. and Powell, Dane} } @article {101, title = {Improved Haptic Fidelity via Reduced Sampling Period with an FPGA-Based Real-Time Hardware Platform }, journal = {ASME Journal of Computing and Information Science in Engineering}, volume = {9}, number = {1}, year = {2009}, note = {Improved Haptic Fidelity Via Reduced Sampling Period With an FPGA-Based Real-Time Hardware Platform}, month = {03/2009}, abstract = {
Marcia K. O{\textquoteright}Malley, Kevin S. Sevcik, and Emilie Kopp, J. Comput. Inf. Sci. Eng. 9, 011002 (2009), DOI:10.1115/1.3072904
A haptic virtual environment is considered to be high-fidelity when the environment is perceived by the user to be realistic. For environments featuring rigid objects, perception of a high degree of realism often occurs when the free space of the simulated environment feels free and when surfaces intended to be rigid are perceived as such. Because virtual surfaces (often called virtual walls) are typically modeled as simple unilateral springs, the rigidity of the virtual surface depends on the stiffness of the spring model. For impedance-based haptic interfaces, the stiffness of the virtual surface is limited by the damping and friction inherent in the device, the sampling rate of the control loop, and the quantization of sensor data. If stiffnesses greater than the limit for a particular device are exceeded, the interaction between the human user and the virtual surface via the haptic device becomes nonpassive. We propose a computational platform that increases the sampling rate of the system, thereby increasing the maximum achievable virtual surface stiffness, and subsequently the fidelity of the rendered virtual surfaces. We describe the modification of a PHANToM Premium 1.0 commercial haptic interface to enable computation by a real-time operating system (RTOS) that utilizes a field programmable gate array (FPGA) for data acquisition between the haptic interface hardware and computer. Furthermore, we explore the performance of the FPGA serving as a standalone system for communication and computation. The RTOS system enables a sampling rate for the PHANToM that is 20 times greater than that achieved using the \“out of the box\” commercial hardware system, increasing the maximum achievable surface stiffness twofold. The FPGA platform enables sampling rates of up to 400 times greater, and stiffnesses over 6 times greater than those achieved with the commercial system. The proposed computational platforms will enable faster sampling rates for any haptic device, thereby improving the fidelity of virtual environments.
}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/101-JCISE\%20proof\%20FINAL\%202-09.pdf}, author = {O{\textquoteright}Malley, M.K. and Sevcik, Kevin S. and Kopp, E} } @proceedings {674, title = {Intermittency of slow arm movements increases in distal direction}, year = {2009}, pages = {4499-4504}, address = {St. Louis, MO}, abstract = {When analyzed in the tangential speed domain, human movements exhibit a multi-peaked speed profile which is commonly interpreted as evidence for submovements. At slow speeds, the number of the peaks increases and the peaks also become more distinct, corresponding to non-smoothness or intermittency in the movement. In this study, we evaluate two potential sources proposed in the literature for the origins of movement intermittency and conclude that intermittency is more likely due to noise in the neuromuscular system as opposed to a central movement planner that generates intermittent plans. This conclusion is based on the assumption that the central planner would be expected to introduce similar levels of intermittency for different joints, while accumulating noise in the neuromuscular circuitry would be expected to exhibit itself as increase in noise in distal direction. We have used a 3D motion capture system to record trajectories of fingertip, wrist, elbow and shoulder as five participants completed a simple manual circular tracking task at various constant speed levels. Statistical analyses indicated that movement intermittency, quantified by a number of peaks metric, increased in distal direction, supporting the noise model for origins of intermittency. Movement speed was determined to have a significant effect on intermittency, while orientation of the task plane showed no significance.
}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/674-Celik2009IROS.pdf}, author = {Ozkan Celik and Gu, Qin and Deng, Zhigang and O{\textquoteright}Malley, M.K.} } @proceedings {108, title = {A Low Cost Vibrotactile Array to Manage Respiratory Motion}, year = {2009}, month = {03/2009}, publisher = {IEEE}, address = {Salt Lake city, Utah}, abstract = {We present a tactile Respiratory Management System (tRMS) to manage and control breathing patterns of cancer patients undergoing radiation therapy. The system comprises of an array of small vibrating motors and a control box that supplies power to and provides a control interface for up to twelve motors through the parallel port of a standard personal computer. The vibrotactile array can be fastened along the forearm, arm, thigh, leg or abdomen in any configuration using Velcro and fabric wraps. All motors are operated in a binary fashion, i.e. on or off, with quick response time and perceivable vibration magnitudes. The tRMS system is inexpensive and portable, providing spatiotemporal variations in tactile cues to regulate respiratory motion during radiotherapy. The system will also be used in future psychophysical studies to determine effective use of tactile cues to control human motor actions.
}, keywords = {Tactile feedback, vibrotactile array}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/108-0236.pdf}, author = {Ali Israr and Dillon P. Eng and Sastry S. Vedam and O{\textquoteright}Malley, M.K.} } @proceedings {528, title = {Movement intermittency and variability in human arm movements}, year = {2009}, pages = {30-31}, address = {Seattle, WA}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/528-Celik2009RSS_workshop_abstract.pdf}, author = {Ozkan Celik and Gu, Qin and Deng, Zhigang and O{\textquoteright}Malley, M.K.} } @article {103, title = {Negative Efficacy of Fixed Gain Error Reducing Shared Control for Training in Virtual Environments}, journal = {ACM Transactions on Applied Perception}, volume = {6}, number = {1}, year = {2009}, month = {01/2009}, abstract = {Virtual reality with haptic feedback provides a safe and versatile practice medium for many manual control tasks. Haptic guidance has been shown to improve performance of manual control tasks in virtual environments; however, the efficacy of haptic guidance for training in virtual environments has not been studied conclusively. This article presents experimental results that show negative efficacy of haptic guidance during training in virtual environments. The haptic guidance in this study is a fixed-gain error-reducing shared controller, with the control effort overlaid on the dynamics of the manual control task during training. Performance of the target-hitting manual control task in the absence of guidance is compared for three training protocols. One protocol contained no haptic guidance and represented virtual practice. Two protocols utilized haptic guidance, varying the duration of exposure to guidance during the training sessions. Exposure to the fixed-gain error-reducing shared controller had a detrimental effect on performance of the target-hitting task at the conclusion of a month-long training protocol, regardless of duration of exposure. While the shared controller was designed with knowledge of the task and an intuitive sense of the motions required to achieve good performance, the results indicate that the acquisition of motor skill is a complex phenomenon that is not aided with haptic guidance during training as implemented in this experiment.
}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/103-Li-Patoglu-O\%27Malley_TAP_6\%281\%29_2009FINAL.pdf}, author = {Yanfang Li and Volkan Patoglu and O{\textquoteright}Malley, M.K.} } @article {102, title = {Passive and Active Discrimination of Natural Frequency of Virtual Dynamic System}, journal = {IEEE Transactions on Haptics}, volume = {2}, number = {1}, year = {2009}, month = {02/2009}, pages = {40-51}, doi = {10.1109/TOH.2008.21}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/102-Israr-Li-Patoglu-O\%27Malley_IEEEToH_2\%281\%29_2009FINAL.pdf}, author = {Ali Israr and Yanfang Li and Volkan Patoglu and O{\textquoteright}Malley, M.K.} } @proceedings {109, title = {Progressive shared control for training in virtual environments}, year = {2009}, month = {03/2009}, pages = {332-337}, publisher = {IEEE}, address = {Salt Lake City, UT, USA}, keywords = {Haptic interface, performance, shared control, training}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/109-LiPSC-WHC.pdf}, author = {Yanfang Li and Joel C. Huegel and Volkan Patoglu and O{\textquoteright}Malley, M.K.} } @proceedings {530, title = {Validation of a smooth movement model for a human reaching task}, year = {2009}, pages = {799-804}, abstract = {This paper presents the experiment design, results, and analysis of a human user study that tests and validates the minimum hand jerk (MHJ) model for a human forearm reaching movement task when manipulating a multi-mass object. This work validates and extends prior work that demonstrated the MHJ criteria, a mathematical approach to human movement modeling, more accurately represents movements with multi-mass objects than the alternate optimally smooth transport (OST) model. To validate the prior work, we developed a visual and haptic virtual environment with a five-mass system with friction connected by springs and viscous dampers. The point to point reaching task we implemented required participants to move their hand with the set of masses to a target position, thereby generating movement profiles for analysis. Our experimental design uniquely extends the application of the MHJ criteria to forearm pronation movements and our results show that the MHJ model holds. Our extension to forearm movements and the more general MHJ criteria are economic models of human movements applicable to fields such as computer animation and virtual environments.
}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/530-Huegel2009ICORRpublished.pdf}, author = {Joel C. Huegel and Lynch, Andrew and O{\textquoteright}Malley, M.K.} } @proceedings {110, title = {Visual Versus Haptic Progressive Guidance For Training In A Virtual Dynamic Task}, year = {2009}, month = {03/2009}, publisher = {IEEE}, address = {Salt Lake City, UT, USA}, keywords = {Haptic interface, training, virtual environment}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/110-Huegel-ProgDemo-WHC.pdf}, author = {Joel C. Huegel and O{\textquoteright}Malley, M.K.} } @proceedings {celik_comparison, title = {Comparison of robotic and clinical motor function improvement measures for sub-acute stroke patients}, year = {2008}, pages = {2477{\textendash}2482}, address = {Pasadena, CA}, abstract = {In this paper, preliminary results in motor function improvement for four sub-acute stroke patients that underwent a hybrid robotic and traditional rehabilitation program are presented. The therapy program was scheduled for three days a week, four hours per day (approximately 60\% traditional constraint induced therapy activities and 40\% robotic therapy). A haptic joystick was used to implement four different operating modes for robotic therapy: unassisted (U), constrained (C), assisted (A), and resisted (R) modes. A target hitting task involving the positioning of a pointer on twelve targets was completed by the patients. Two different robotic measures were utilized to quantify the motor function improvement through the sessions: trajectory error (TE) and smoothness of movement (SM). Fugl-Meyer (FM) and motor activity log (MAL) scales were used as clinical measures. Analysis of results showed that the group demonstrates a significant motor function improvement with respect to both clinical and robotic measures. Regression analyses were carried out on corresponding clinical and robotic measure result pairs. A significant relation between FM scale and robotic measures was found for both of the analyzed modes. Regression of robotic measures on MAL scores resulted in no significance. A regression analysis that compared the two clinical measures revealed a very low agreement. Our findings suggest that it might be possible to obtain objective robotic measures that are significantly correlated to widely-used and reliable clinical measures in considerably different operating modes and control schemes.
}, keywords = {robotic rehabilitation}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/74-CelikICRA2008.pdf}, author = {Ozkan Celik and O{\textquoteright}Malley, M.K. and Boake, Corwin and H.S. Levin and Fischer, Steven and Reistetter, Timothy} } @article {080611080561, title = {Design, control and performance of RiceWrist: A force feedback wrist exoskeleton for rehabilitation and training}, journal = {International Journal of Robotics Research}, volume = {27}, number = {2}, year = {2008}, note = {Feedback wrist exoskeleton;Neurological injuries;
}, pages = {233 - 251}, abstract = {This paper presents the design, control and performance of a high fidelity four degree-of-freedom wrist exoskeleton robot, RiceWrist, for training and rehabilitation. The RiceWrist is intended to provide kinesthetic feedback during the training of motor skills or rehabilitation of reaching movements. Motivation for such applications is based on findings that show robot-assisted physical therapy aids in the rehabilitation process following neurological injuries. The exoskeleton device accommodates forearm supination and pronation, wrist flexion and extension and radial and ulnar deviation in a compact parallel mechanism design with low friction, zero backlash and high stiffness. As compared to other exoskeleton devices, the RiceWrist allows easy measurement of human joint angles and independent kinesthetic feedback to individual human joints. In this paper, joint-space as well as task-space position controllers and an impedance-based force controller for the device are presented. The kinematic performance of the device is characterized in terms of its workspace, singularities, manipulability, backlash and backdrivability. The dynamic performance of RiceWrist is characterized in terms of motor torque output, joint friction, step responses, behavior under closed loop set-point and trajectory tracking control and display of virtual walls. The device is singularity-free, encompasses most of the natural workspace of the human joints and exhibits low friction, zero-backlash and high manipulability, which are kinematic properties that characterize a high-quality impedance display device. In addition, the device displays fast, accurate response under position control that matches human actuation bandwidth and the capability to display sufficiently hard contact with little coupling between controlled degrees-of-freedom.
}, keywords = {Control systems, Degrees of freedom (mechanics), Feedback, Neurology, Physical therapy, Systems analysis}, url = {http://dx.doi.org/10.1177/0278364907084261}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/48-IJRR-Feb-2008-small.pdf}, author = {Abhishek Gupta and O{\textquoteright}Malley, M.K. and Volkan Patoglu and Burgar, Charles} } @inbook {105, title = {Haptic Interfaces}, booktitle = {HCI: Beyond the GUI}, year = {2008}, pages = {25-74}, publisher = {Morgan-Kaufman Publisher}, organization = {Morgan-Kaufman Publisher}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/105-Kortum02Gupta-O\%27Malley.pdf}, author = {O{\textquoteright}Malley, M.K. and Abhishek Gupta} } @proceedings {9872945, title = {Passive and active kinesthetic perception just-noticeable-difference for natural frequency of virtual dynamic systems}, year = {2008}, note = {active kinesthetic perception;passive kinesthetic perception;just-noticeable-difference;virtual second order dynamic systems;degree-of-freedom haptic device;haptic sensory feedback;virtual resonance task;visual feedback;
}, month = {03/2008}, pages = {25 - 31}, publisher = {IEEE}, address = {Reno, NE, USA}, abstract = {This paper investigates the just-noticeable-difference (JND) for natural frequency of virtual second order dynamic systems. Using a one degree-of-freedom haptic device, visual and/or haptic sensory feedback were presented during interactions with the system. Participants were instructed to either perceive passively or actively excite the system in order to discriminate natural frequencies. The JND for this virtual resonance task ranged from 3.99 \% to 6.96 \% for reference frequencies of 1 Hz and 2 Hz. Results show that sensory feedback has a significant effect on JND in passive perception, with combined visual and haptic feedback enabling the best discrimination performance. In active perception, there is no significant difference on JND with haptic and combined visual and haptic feedback. There is also no significant difference between active perception and passive perception for this JND experiment. The presentation of systems with equivalent natural frequencies but different spring stiffness resulted in no large bias toward larger stiffness and no significant difference in JND for equivalent systems. This finding indicates that human participants do not discriminate natural frequency based on the maximum force magnitude perceived, as indicated by prior studies.
}, keywords = {Haptic interfaces, visual perception}, issn = {978-1-4244-2005-6}, doi = {10.1109/HAPTICS.2008.4479908}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4479908}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/58-HapticSymposium2008_Li.pdf}, author = {Yanfang Li and Ali Israr and Volkan Patoglu and O{\textquoteright}Malley, M.K.} } @proceedings {082211289622, title = {Disturbance observer based closed loop force control for haptic feedback}, volume = {9 PART B}, year = {2007}, note = {Disturbance observer;Haptic feedback;Pseudostatic interactions;
}, pages = {1343 - 1349}, address = {Seattle, WA, United States}, abstract = {Most commonly used impedance-type haptic interfaces employ open-loop force control under the assumption of pseudostatic interactions. Advanced force control in such interfaces can increase simulation fidelity through improvement of the transparency of the device, and can further improve robustness. However, closed loop force-feedback is limited both due to the bandwidth limitations of force sensing and the associated cost of force sensors required for its implementation. In this paper, we propose the use of a nonlinear disturbance observer for estimation of contact forces during haptic interactions. This approach circumvents the traditional drawbacks of force sensing while exhibiting the advantages of closed-loop force control in haptic devices. The feedback of contact force information further enables implementation of advanced robot force control techniques such as robust hybrid impedance and admittance control. Simulation and experimental results, utilizing a PHANToM Premium 1.0A haptic interface, are presented to demonstrate the efficacy of the proposed approach. Copyright {\textcopyright} 2007 by ASME.
}, keywords = {Computer simulation, Force control, Haptic interfaces, Robotics, Robustness (control systems)}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/50-gupta-imece07.pdf}, author = {Abhishek Gupta and O{\textquoteright}Malley, M.K. and Volkan Patoglu} } @proceedings {082211289621, title = {Improved haptic fidelity via reduced sampling period with an FPGA-based real-time hardware platform (IMECE)}, volume = {9 PART B}, year = {2007}, note = {Real Time Operating System (RTOS) control system;Proprietary control card;
}, pages = {1335 - 1342}, address = {Seattle, WA, United States}, abstract = {Impedance based haptic interfaces face inherent challenges in displaying stiff virtual environments. Fidelity of a virtual environment is enhanced by stiff virtual walls combined with low damping and passive behavior of the interface. However, the stiffness of virtual walls displayed on an impedance based interface is limited by the damping inherent in the controller, the sampling rate of the control loop, and the quantization of the controller{\textquoteright}s position. Attempting to display a stiffness larger than this limiting value destroys the passivity of the interface, leading to active controller behavior and eventually closed loop instability. We propose a method of increasing the fidelity of a PHANToM Premium 1.0 commercial haptic interface by controlling it via a Field Programmable Gate Array (FPGA) both alone and with a Real Time Operating System (RTOS) control system. This custom controller enjoys several benefits over the standard control achieved via a proprietary control card in a Multitasking OS, including reduced system overhead and deterministic loop rate timing. The performance of the proposed FPGA/RTOS controller compares favorably with the performance of an FPGA/Multitasking OS controller. The FPGA/RTOS controller achieves control loop rates an order of magnitude greater than that of the proprietary controller, allowing virtual walls to be displayed with greatly increased stiffnesses, while retaining the passivity and low damping of the PHANToM interface. Copyright {\textcopyright} 2007 by ASME.
}, keywords = {Computer operating systems, Damping, Field programmable gate arrays (FPGA), Multitasking, Real time systems, Virtual reality}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/56-IMECE2007-42085.pdf}, author = {Sevcik, Kevin S. and Kopp, E and O{\textquoteright}Malley, M.K.} } @proceedings {mcstravick2007im, title = {Improving Interdisciplinary Capstone Design Projects with Cooperative Learning in the Medi-Fridge Project}, year = {2007}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/mcstravick2007asee.pdf}, author = {Mcstravick, David and O{\textquoteright}Malley, Marcia K.} } @inbook {104, title = {Principles of human-machine interfaces and interactions}, booktitle = {Life Science Automation: Fundamentals and Applications}, year = {2007}, pages = {101-125}, publisher = {Artech House Publishers}, organization = {Artech House Publishers}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/omalley2007lifescienceauto.pdf}, author = {O{\textquoteright}Malley, M.K.} } @inbook {106, title = {Robotic Exoskeletons for Upper Extremity Rehabilitation}, booktitle = {Rehabilitation Robotics}, year = {2007}, pages = {371-396}, publisher = {I-Tech Education and Publishing}, organization = {I-Tech Education and Publishing}, address = {Vienna, Austria}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/106-robotic_exoskeletons_Gupta_O\%27Malley.pdf}, author = {Abhishek Gupta and O{\textquoteright}Malley, M.K.} } @proceedings {073510787453, title = {Towards just noticeable differences for natural frequency of manually excited virtual dynamic systems}, year = {2007}, note = {Graphical displays;Virtual mass spring systems;Dynamic properties;
}, month = {03/2007}, pages = {569 - 570}, publisher = {IEEE}, address = {Tsukuba, Japan}, abstract = {This paper explores the experiment design to determine a human{\textquoteright}s ability to discriminate the natural frequency of manually excited virtual dynamic systems. We use a one degree-of-freedom haptic interface with a coupled graphical display to render a virtual mass-spring system, which is excited by the human operator using his/her dominant hand. The results from the preliminary experiment indicate a JND value of approximately 8\%. However, results also indicate that excitation strategies have a significant effect on the discrimination threshold determination of this dynamic property. In this paper, along with a discussion of the preliminary results, a refined experiment design that accounts for different factors influencing the discrimination of manually excited natural frequency is presented. {\textcopyright} 2007 IEEE.
}, keywords = {Display devices, Dynamical systems, Natural frequencies}, doi = {10.1109/WHC.2007.118}, url = {http://dx.doi.org/10.1109/WHC.2007.118}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/59-00\%20-\%20Towards\%20Just\%20Noticeable\%20Differences\%20for\%20Natural\%20Frequency\%20of\%20Manually\%20Excited\%20Virtual\%20Dynamic\%20Systems.pdf}, author = {Yanfang Li and Volkan Patoglu and Huang, Deborah and O{\textquoteright}Malley, M.K.} } @proceedings {064610244127, title = {Adaptation of Haptic Interfaces for a LabVIEW-based System Dynamics Course}, year = {2006}, note = {Electromechanical systems;LabVIEW graphical programming languages;
}, pages = {147 - 152}, address = {Alexandria, VA, United States}, abstract = {This paper describes the development of haptic paddle laboratory kits and associated National Instruments LabVIEW virtual instrumentation to support the adaptation of laboratory experiments for a required undergraduate system dynamics course at Rice University. The laboratory experiments use simple haptic interfaces, devices that allow the students to interact via the sense of touch with virtual environments. A clear benefit of this laboratory series is that students study the haptic paddle as a real electromechanical system in addition to using the haptic paddle as a tool to interact with virtual mechanical systems. The haptic paddle hardware has been modified to improve robustness, and the LabVIEW graphical programming language is used for data acquisition and control throughout the laboratory series. {\textcopyright} 2006 IEEE.
}, keywords = {Computer hardware, Curricula, Dynamic programming, Interactive computer systems, Virtual reality}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/35-getPDF.pdf}, author = {Kevin Bowen and O{\textquoteright}Malley, M.K.} } @article {14, title = {Assessing and Inducing Neuroplasticity with TMS and Robotics}, journal = {Archives of Physical Medicine and Rehabilitation, Supplement 2 / Neuroplasticity and Brain Imaging Research: Implications for Rehabilitation}, volume = {87(12)}, year = {2006}, pages = {59-66}, url = {http://linkinghub.elsevier.com/retrieve/pii/S0003999306012792}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/14-PIIS0003999306012792.pdf}, author = {O{\textquoteright}Malley, M.K. and T. Ro and H.S. Levin} } @article {o2006assessing, title = {Assessing and inducing neuroplasticity with transcranial magnetic stimulation and robotics for motor function}, journal = {Archives of physical medicine and rehabilitation}, volume = {87}, number = {12}, year = {2006}, month = {12/2006}, pages = {59{\textendash}66}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/omalley2006neuroplasticity.pdf}, author = {O{\textquoteright}Malley, Marcia K and Ro, Tony and Levin, Harvey S} } @article {071210493824, title = {Design of a haptic arm exoskeleton for training and rehabilitation}, journal = {IEEE/ASME Transactions on Mechatronics}, volume = {11}, number = {3}, year = {2006}, note = {Arm exoskeletons;Apparent inertia;Design methodology;
}, pages = {280 - 289}, abstract = {A high-quality haptic interface is typically characterized by low apparent inertia and damping, high structural stiffness, minimal backlash, and absence of mechanical singularities in the workspace. In addition to these specifications, exoskeleton haptic interface design involves consideration of space and weight limitations, workspace requirements, and the kinematic constraints placed on the device by the human arm. These constraints impose conflicting design requirements on the engineer attempting to design an arm exoskeleton. In this paper, the authors present a detailed review of the requirements and constraints that are involved in the design of a high-quality haptic arm exoskeleton. In this context, the design of a five-degree-of-freedom haptic arm exoskeleton for training and rehabilitation in virtual environments is presented. The device is capable of providing kinesthetic feedback to the joints of the lower arm and wrist of the operator, and will be used in future work for robot-assisted rehabilitation and training. Motivation for such applications is based on findings that show robot-assisted physical therapy aids in the rehabilitation process following neurological injuries. As a training tool, the device provides a means to implement flexible, repeatable, and safe training methodologies. \© 2006 IEEE.
}, keywords = {Damping, Degrees of freedom (mechanics), Joints (anatomy), Patient rehabilitation, Robot applications, Sensory perception, Stiffness}, url = {http://dx.doi.org/10.1109/TMECH.2006.875558}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/47-IEEEASME_HapticArmExoskeleton.pdf}, author = {Abhishek Gupta and O{\textquoteright}Malley, M.K.} } @proceedings {072310640904, title = {Experimental system identification of force reflecting hand controller}, year = {2006}, note = {Manipulator design;Environmental impedance;Sinusoidal sweep torque input;
}, pages = {9 -}, address = {Chicago, IL, United States}, abstract = {This paper describes the combined time and frequency domain identification of the first three degrees-of-freedom (DOF) of a six degree-of-freedom force reflecting hand controller (FRHC). The FRHC is used to teleoperate Robonaut, a humanoid robotic assistant developed by NASA, via a bilateral teleoperation architecture. Three of the six DOF of the FRHC are independently identified due to the decoupled nature of the manipulator design. The frequency response for each axis is acquired by coupling a known environmental impedance to the joint axis and then applying a sinusoidal sweep torque input. Several data sets are averaged in the frequency domain to obtain an averaged frequency response. A coherence analysis is then performed and data with low coherence values are ignored for subsequent analysis and model fitting. The paper describes the use of coherence data to ensure acceptable model fits for transfer function estimation. Results of the identification experiments are presented, including implications of assumptions of decoupling and linearity. In addition, frequency and time domain validations for each axis model are performed using data sets excluded from the parameter estimation, with strong correlation. Copyright {\textcopyright} 2006 by ASME.
}, keywords = {Degrees of freedom (mechanics), Force measurement, Frequency domain analysis, Identification (control systems), Remote control, Robotics}, author = {Zumbado, Fernando and McJunkin, Samuel and O{\textquoteright}Malley, M.K.} } @proceedings {075210997323, title = {Haptic Interfaces for a LabVIEW-based System Dynamics Course}, year = {2006}, note = {Labview;Course content;Laboratory exercises;Haptic paddles;
}, address = {Chicago, IL, United States}, abstract = {Too often in undergraduate mechanical engineering courses, the content of laboratory exercises is not well coordinated with course content, and the exercises are unrelated to each other. As a result, students have a difficult time grasping the "big picture" themes. This project at Rice University seeks to improve the effectiveness of laboratory exercises in a required undergraduate mechanical engineering system dynamics course via student-centered learning and laboratory topics featuring haptic paddles, devices that allow users to interact via the sense of touch with virtual environments. One outcome of these improvements is a cohesive set of laboratory experiments using the haptic paddles as a single experimental test bed for multiple experiments. The Haptic Paddle exercises are unique because they allow the students to analyze and build their own haptic interface, or force-reflecting system. The students are able to see many subsets of mechanical engineering come together in a series of exercises, including assembly, system analysis, calibration, system modeling, and dynamics. Finally, a key advantage to the haptic paddle labs is that they tie closely with the course material. This paper describes the development of haptic paddle laboratory kits and associated National Instruments LabVIEW virtual instrumentation to support the adaptation of laboratory experiments for a required undergraduate system dynamics course at Rice University. The laboratory experiments use simple haptic interfaces, devices that allow the students to interact via the sense of touch with virtual environments. A clear benefit of this laboratory series is that students study the haptic paddle as a real electromechanical system in addition to using the haptic paddle as a tool to interact with virtual mechanical systems. The haptic paddle hardware has been modified to improve robustness, and the LabVIEW graphical programming language is used for data acquisition and control throughout the laboratory series. The paper will present some details of the laboratory components, and preliminary assessment of learning outcomes using this laboratory series compared to more traditional modular labs used in prior years. {\textcopyright} American Society for Engineering Education, 2006.
}, keywords = {Computer programming languages, Electromechanical devices, Engineering education, Learning systems, Mechanical engineering, Students, Virtual reality}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/36-ASEE2006-paper-O\%27Malley\%20session\%201526.pdf}, author = {Kevin Bowen and O{\textquoteright}Malley, M.K.} } @proceedings {sledd_perf_2006, title = {Performance Enhancement of a Haptic Arm Exoskeleton}, year = {2006}, pages = {375{\textemdash}381}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/68-SleddOMalleyHAPTICS06final.pdf}, author = {Alan Sledd and O{\textquoteright}Malley, M.K.} } @proceedings {072310640980, title = {The RiceWrist: A distal upper extremity rehabilitation robot for stroke therapy}, year = {2006}, note = {Mirror Image Movement Enabler (MIME) system;Rehabilitation robot;Robotic therapy;
}, month = {11/2006}, pages = {10 -}, publisher = {ASME}, address = {Chicago, IL, United States}, abstract = {This paper presents the design and kinematics of a four degree-of-freedom upper extremity rehabilitation robot for stroke therapy, to be used in conjunction with the Mirror Image Movement Enabler (MIME) system. The RiceWrist is intended to provide robotic therapy via force-feedback during range-of-motion tasks. The exoskeleton device accommodates forearm supination and pronation, wrist flexion and extension, and radial and ulnar deviation in a compact design with low friction and backlash. Joint range of motion and torque output of the electricmotor driven device is matched to human capabilities. The paper describes the design of the device, along with three control modes that allow for various methods of interaction between the patient and the robotic device. Passive, triggered, and active-constrained modes, such as those developed for MIME, allow for therapist control of therapy protocols based on patient capability and progress. Also presented is the graphical user interface for therapist control of the interactions modes of the RiceWrist, basic experimental protocol, and preliminary experimental results. Copyright {\textcopyright} 2006 by ASME.
}, keywords = {Degrees of freedom (mechanics), Graphical user interfaces, Human rehabilitation equipment, Patient treatment}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/46-00\%20-\%20IMECE2006-16103-O\%27Malley.pdf}, author = {O{\textquoteright}Malley, M.K. and Alan Sledd and Abhishek Gupta and Volkan Patoglu and Joel C. Huegel and Burgar, Charles} } @proceedings {li_shared_2006, title = {Shared Control for Training in Virtual Environments: Learning Through Demonstration?}, year = {2006}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/73-00\%20-\%20Li_Patoglu_OMalley_Eurohaptics06.pdf}, author = {Yanfang Li and Volkan Patoglu and O{\textquoteright}Malley, M.K.} } @article {06199869875, title = {Shared control in haptic systems for performance enhancement and training}, journal = {Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME}, volume = {128}, number = {1}, year = {2006}, note = {Virtual environments;Mass-spring-damper;System dynamics;Shared control;
}, pages = {75 - 85}, chapter = {75}, abstract = {This paper presents a shared-control interaction paradigm for haptic interface systems, with experimental data from two user studies. Shared control, evolved from its initial telerobotics applications, is adapted as a form of haptic assistance in that the haptic device contributes to execution of a dynamic manual target-hitting task via force commands from an automatic controller. Compared to haptic virtual environments, which merely display the physics of the virtual system, or to passive methods of haptic assistance for performance enhancement based on virtual fixtures, the shared-control approach offers a method for actively demonstrating desired motions during virtual environment interactions. The paper presents a thorough review of the literature related to haptic assistance. In addition, two experiments were conducted to independently verify the efficacy of the shared-control approach for performance enhancement and improved training effectiveness of the task. In the first experiment, shared control is found to be as effective as virtual fixtures for performance enhancement, with both methods resulting in significantly better performance in terms of time between target hits for the manual target-hitting task than sessions where subjects feel only the forces arising from the mass-spring-damper system dynamics. Since shared control is more general than virtual fixtures, this approach may be extremely beneficial for performance enhancement in virtual environments. In terms of training enhancement, shared control and virtual fixtures were no better than practice in an unassisted mode. For manual control tasks, such as the one described in this paper, shared control is beneficial for performance enhancement, but may not be viable for enhancing training effectiveness. Copyright \© 2006 by ASME.
}, keywords = {Control equipment, Damping, Data reduction, Haptic interfaces, Robotics, Robots}, issn = {0022-0434}, doi = {10.1115/1.2168160 }, url = {http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal\&id=JDSMAA000128000001000075000001\&idtype=cvips\&gifs=yes}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/52-00\%20-\%20JDSMC\%20Shared\%20control.pdf}, author = {O{\textquoteright}Malley, M.K. and Abhishek Gupta and Gen, Matthew and Yanfang Li} } @article {71, title = {A Study of Perceptual Performance in Haptic Virtual Environments}, journal = {Journal of Robotics and Mechatronics}, volume = {18(4)}, year = {2006}, pages = {467-475}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/71-Rb18-4-2617.pdf}, author = {O{\textquoteright}Malley, M.K. and Gina Upperman} } @proceedings {072310640927, title = {Vision based force sensing for nanorobotic manipulation}, year = {2006}, note = {Nanomanipulation;Nanoassembly;
}, pages = {10 -}, address = {Chicago, IL, United States}, abstract = {Over the last decade, considerable interest has been generated in building and manipulating nanoscale structures. Applications of nanomanipulation include study of nanoparticles, molecules, DNA and viruses, and bottom-up nanoassembly. We propose a Nanomanipulation System using the Zyvex S100 nanomanipulator, -which operates within a scanning electron microscope (SEM), as its primary component. The primary advantage of the S100 setup over standard scanning probe microscopy based nanomanipulators is the ability to see the object during manipulation. Relying on visual feedback alone to control the nanomanipulator is not preferable due to perceptual limitations of depth and contact within the SEM. To improve operator performance over visual feedback alone, an impedance-controlled bilateral teleoperation setup is envisioned. Lack of on-board force sensors on the S100 system is the primary hindrance in the realization of the proposed architecture. In this paper, we present a computer vision based force sensing scheme. The advantages of this sensing strategy include its low cost and lack of requirement of hardware modifications). Force sensing is implemented using an atomic force microscopy (AFM) probe attached to the S100 end-effector. Deformation of the cantilever probe is monitored using a Hough transform based algorithm. These deformations are mapped to corresponding end-effector forces following the Euler-Bernoulli beam mechanics model. The forces thus sensed can be used to provide force-feedback to the operator through a master manipulator. Copyright {\textcopyright} 2006 by ASME.
}, keywords = {Atomic force microscopy, Force measurement, Manipulators, Nanoparticles, Nanotechnology, Scanning electron microscopy}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/49-IMECE2006-15111-Gupta-small.pdf}, author = {Abhishek Gupta and Volkan Patoglu and O{\textquoteright}Malley, M.K.} } @article {8627855, title = {On the ability of humans to haptically identify and discriminate real and simulated objects}, journal = {Presence (USA)}, volume = {14}, number = {3}, year = {2005}, note = {real object;simulated object;human subject;haptic interface;haptic simulation;size-identification task;virtual surface stiffness;}, pages = {366 - 76}, abstract = {The ability of human subjects to identify and discriminate between different-sized real objects was compared with their ability to identify and discriminate between different-sized simulated objects generated by a haptic interface. This comparison was additionally performed for cases of limited force and limited stiffness output from the haptic device, which in effect decrease the fidelity of the haptic simulation. Results indicate that performance of size-identification tasks with haptic-interface hardware capable of a minimum of 3 N of maximum force output can approach performance in real environments, but fails short when virtual surface stiffness is limited. For size-discrimination tasks, performance in simulated environments was consistently lower than performance in a comparable real environment. Interestingly, significant variations in the fidelity of the haptic simulation do not appear to significantly alter the ability of a subject to identify or discriminate between the types of simulated objects described herein
}, keywords = {Haptic interfaces, Virtual reality}, url = {http://dx.doi.org/10.1162/105474605323384690}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/omalley2005teleop.pdf}, author = {O{\textquoteright}Malley, M.K. and Michael Goldfarb} } @proceedings {8529772, title = {Human-machine admittance and transparency adaptation in passive user interaction with a haptic interface}, year = {2005}, note = {human-machine admittance;transparency adaptation;passive user interaction;haptic interface;force amplitude;passive user induced interactions;event-based haptic interactions;virtual environments;force amplitudes;transparency bandwidth;
}, month = {03/2005}, pages = {283 - 9}, address = {Pisa, Italy}, abstract = {This paper addresses human adaptation to changes in coupling impedance and force amplitude during passive user induced (PUI) interactions with a haptic interface. PUI interactions are characterized as event-based haptic interactions or haptic recordings that are replayed to the user. In the study, virtual environments are displayed to passive users with variable coupling stiffness and force amplitudes, and transparency bandwidth and human-machine admittance are measured. Results indicate that transparency bandwidth and the human-machine admittance do not change significantly for permutations of force amplitudes and coupling impedances, nor do they vary significantly across users. The reason for this invariance is that, during a PUI interaction, users tend approach a similar displacement profile. As a result, all users will have similar apparent admittance and transparency. The findings give sufficient justification for the use of universal compensators that improve transparency bandwidth, and that can be designed based solely on a priori transparency measurements for a typical user
}, keywords = {Haptic interfaces, Human computer interaction, Manipulators, Virtual reality}, doi = {10.1109/WHC.2005.76}, url = {http://www2.computer.org/portal/web/csdl/doi/10.1109/WHC.2005.76}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/64-00\%20-\%20Human-machine\%20admittance\%20and\%20transparency\%20adaptation\%20in\%20passive\%20user\%20interaction\%20with\%20-\%20mcjunk.pdf}, author = {McJunkin, Samuel and Yanfang Li and O{\textquoteright}Malley, M.K.} } @proceedings {omalley_sh_2005, title = {Shared control for upper extremity rehabilitation in virtual environments}, year = {2005}, month = {11/2015}, pages = {pp 1673-1681}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/omalley2005asmeshared.pdf}, author = {O{\textquoteright}Malley, M.K.} } @proceedings {06169823659, title = {Transparency extension in haptic interfaces via adaptive dynamics cancellation}, volume = {74 DSC}, number = {2 PART B}, year = {2005}, note = {Transparency extension;Robotic manipulators;Transparency transfer function (TTF);Model cancellation techniques;
}, pages = {1581 - 1587}, address = {Orlando, FL, United States}, abstract = {Haptic interfaces are a class of robotic manipulators that display force feedback to enhance the realism of virtual environment displays. However, these manipulators often fail to effectively replicate the real world environment due to dynamic limitations of the manipulator itself. The ratio of the simulated to transmitted environment impedance is defined as the transparency transfer function (TTF), and can be used to quantify the effectiveness of a haptic device in displaying the simulated environment. The TTF is ideally equal to one for the bandwidth of human proprioception. In this work, a method is presented that increases TTF bandwidth via cancellation of dynamics with an adaptive model. This adaptive model is based on the kinematics and dynamics of a PHANToM haptic interface with assumed joint stiffness and damping added. The Lagrangian of the PHANToM is reformulated into a regressor matrix containing the state variables multiplied by a parameter vector. A least-squares approach is used to estimate the parameter vector by assuming that errors in force output are due to the manipulator dynamics. The parameter estimate is then used in the original model to provide a feed-forward cancellation of the manipulator dynamics. Software simulation using data from passive user interactions shows that the model cancellation technique improves bandwidth up to 35 Hz versus 7 Hz without compensation. Finally, this method has a distinct advantage when compared with other compensation methodsfor haptic interactions because it does not rely on linear assumptions near a particular operating point and will adapt to capture unmodeled features. Copyright {\textcopyright} 2005 by ASME.
}, keywords = {Adaptive control systems, Computer simulation, Linear systems, Manipulators, Mathematical models, Transfer functions}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/mcjunkin2005asme.pdf}, author = {McJunkin, Samuel and Speich, John E. and O{\textquoteright}Malley, M.K.} } @proceedings {05359336514, title = {Transparency of a phantom premium haptic interface for active and passive human interaction}, volume = {5}, year = {2005}, note = {Active user induced (AUI);Phantom manipulators;Human operators;
}, pages = {3060 - 3065}, address = {Portland, OR, United States}, abstract = {This paper compares two methods for determining the transparency bandwidth of an impedance based haptic interface with a Phantom 1.0A haptic device. Active user induced (AUI) interaction tests, where the system excitation is generated by a human user, show that transparency bandwidth is limited to approximately 2 Hz. Passive user induced (PUI) interaction tests, where the system excitation is generated by the haptic device with a passive human operator, show that bandwidth can extend up to 50 Hz. Experimental results show that the apparent bandwidth limitations for the AUI interaction tests are dependent on the human user{\textquoteright}s inability to excite higher frequencies. Consequently, this measurement approach is insufficient for determining system bandwidth of the human operator-haptic interface system. Furthermore, data seem to indicate that there is no appreciable difference in the ability of the Phantom manipulator to display environmental impedances in either AUI or PUI interactions regardless of the user. {\textcopyright} 2005 AACC.
}, keywords = {Acoustic impedance, Bandwidth, Manipulators}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/60-Full\%20Text.pdf}, author = {McJunkin, Samuel and O{\textquoteright}Malley, M.K. and Speich, John E.} } @proceedings {06169823803, title = {Virtual lab for system identification of an electromechanical system}, volume = {74 DSC}, number = {1 PART A}, year = {2005}, note = {Virtual instrument (vi);Identification laboratory;Virtual Lab (VL);
}, pages = {705 - 712}, address = {Orlando, FL, United States}, abstract = {A stand-alone virtual instrument (vi) has been developed to augment an experimental system identification laboratory exercise in a required mechanical engineering course on system dynamics. The Virtual Lab (VL) was used productively as a post-lab exercise in conjunction with an existing laboratory experiment for system identification. The VL can be formatted as a standalone file, which the students can download and access at their convenience, without the need for LabVIEW software. The virtual lab presented in this paper used the experimental identification of a transfer function for an xy recorder developed at Rose-Hulman Institute of Technology. In the original Rose-Hulman experiment, students view a video of the acquisition of frequency response data for an X-Y recorder. Then, students complete a detailed optimization procedure using Microsoft Excel in order to determine system parameters for two transfer function models. This paper describes using the Virtual Lab to extend the original lab exercise into an interactive mode. The students complete the Microsoft Excel part of the exercise, but then repeat the optimization using brute force via the LabVIEW based VL developed by the authors, rather than using the optimization toolbox in Excel. With the VL, students can see in real-time the effects of each unknown parameter on the frequency response plot, thus providing additional insight into the relationships between these parameters and the behavior of the electromechanical system. This feature is notably absent in the Microsoft Excel portion of the exercise. Although this exercise uses simple dynamic models, the combination of Excel and LabVIEW approaches provide an insightful introduction to experimental system identification. In this paper, details of the VL are presented, including the functionality of the VL and methodologies for disseminating the VL as a stand-alone piece of software. Finally some assessment results for the original (Excel version) and VL methods of presenting the laboratory exercise are discussed. Copyright {\textcopyright} 2005 by ASME.
}, keywords = {Computer software, Data acquisition, Mathematical models, Mechanical engineering, Real time systems, Students}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/omalley2005asme.pdf}, author = {O{\textquoteright}Malley, M.K. and David M. McStravick} } @proceedings {04278244649, title = {Comparison of human haptic size discrimination performance in simulated environments with varying levels of force and stiffness}, year = {2004}, note = {Size discrimination experiments;Machine quality;Haptic devices;
}, pages = {169 - 175}, address = {Chicago, IL, United States}, abstract = {The performance levels of human subjects in size discrimination experiments in virtual environments with varying levels of stiffness and force saturation are presented. The virtual environments are displayed with a Phantom desktop three degree-of-freedom haptic interface. Performance was measured at below maximum machine performance levels for two machine parameters: maximum endpoint force and maximum virtual surface stiffness. The tabulated scores for the size discrimination in the sub-optimal virtual environments, except for those of the lowest stiffness, 100 N/m, were found to be comparable to that in the highest-quality virtual environment. This supports previous claims that haptic interface hardware may be able to convey, for this perceptual task, sufficient perceptual information to the user with relatively low levels of machine quality in terms of these parameters, as long as certain minimum levels, 1.0 N force and 220 N/m stiffness, are met.
}, keywords = {Computer simulation, Computer software, Degrees of freedom (mechanics), Feedback, Haptic interfaces, Human engineering, Stiffness}, url = {http://dx.doi.org/10.1109/HAPTIC.2004.1287193}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/upperman2004haptics.pdf}, author = {Gina Upperman and Suzuki, Atsushi and O{\textquoteright}Malley, M.K.} } @proceedings {04278244642, title = {Cooperative manipulation between humans and teleoperated agents}, year = {2004}, note = {Robonauts;Haptic feedback;Cooperative manipulation;
}, pages = {114 - 120}, address = {Chicago, IL, United States}, abstract = {Robonaut is a humanoid robot designed by the Robotic Systems Technology Branch at NASA{\textquoteright}s Johnson Space Center in a collaborative effort with DARPA. This paper describes the implementation of haptic feedback into Robonaut. We conducted a cooperative manipulation task, inserting a flexible beam into an instrumented receptacle. This task was performed while both a human at the worksite and the teleoperated robot grasped the flexible beam simultaneously. Peak forces in the receptacle were consistently lower when the human operator was provided with kinesthetic force feedback in addition to other modalities of feedback such as gestures and voice commands. These findings are encouraging as the Dexterous Robotics Lab continues to implement force feedback into its teleoperator hardware architecture.
}, keywords = {Computer simulation, Feedback, Haptic interfaces, Human computer interaction, Robots, Statistical methods}, url = {http://dx.doi.org/10.1109/HAPTIC.2004.1287185}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/glassmire2004haptics.pdf}, author = {John Glassmire and O{\textquoteright}Malley, M.K. and William Bluethmann and Robert O. Ambrose} } @proceedings {05239144488, title = {Design of a haptic arm exoskeleton for training and rehabilitation}, volume = {73}, number = {2 PART B}, year = {2004}, note = {Haptic arm exoskeleton;Inertia;Structural stiffness;Kinesthetic feedback;
}, pages = {1011 - 1018}, address = {Anaheim, CA, United States}, abstract = {A high-quality haptic interface is typically characterized by low apparent inertia and damping, high structural stiffness, minimal backlash and absence of mechanical singularities in the workspace. In addition to these specifications, exoskeleton haptic interface design involves consideration of additional parameters and constraints including space and weight limitations, workspace requirements and the kinematic constraints placed on the device by the human arm. In this context, we present the design of a five degree-of-freedom haptic arm exoskeleton for training and rehabilitation in virtual environments. The design of the device, including actuator and sensor selection, is discussed. Limitations of the device that result from the above selections are also presented. The device is capable of providing kinesthetic feedback to the joints of the lower arm and wrist of the operator, and will be used in future work for robot-assisted rehabilitation and training. Copyright {\textcopyright} 2004 by ASME.
}, keywords = {Actuators, Bandwidth, Damping, Degrees of freedom (mechanics), Friction, Human computer interaction, Kinematics, Robotic arms, Robots, Sensors, Stiffness}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/gupta2004asme.pdf}, author = {Abhishek Gupta and O{\textquoteright}Malley, M.K.} } @article {04338307919, title = {The effect of virtual surface stiffness on the haptic perception of detail}, journal = {IEEE/ASME Transactions on Mechatronics}, volume = {9}, number = {2}, year = {2004}, note = {Virtual surface stiffness;Haptic perception;Design specifications;Haptic interface hardware;
}, pages = {448 - 454}, abstract = {This brief presents a quantitative study of the effects of virtual surface stiffness in a simulated haptic environment on the haptic perception of detail. Specifically, the haptic perception of detail is characterized by identification, detection, and discrimination of round and square cross section ridges. Test results indicate that performance, measured as a percent correct score in the perception experiments, improves in a nonlinear fashion as the maximum level of virtual surface stiffness in the simulation increases. Further, test subjects appeared to reach a limit in their perception capabilities at maximum stiffness levels of 300 to 400 N/m, while the hardware was capable of 1000 N/m of maximum virtual surface stiffness. These results indicate that haptic interface hardware may be able to convey sufficient perceptual information to the user with relatively low levels of virtual surface stiffness. \© 2004 IEEE.
}, keywords = {Computer aided design, Computer hardware, Computer simulation, Degrees of freedom (mechanics), Manipulators, Object recognition, Sensory perception, Specifications, Stiffness, Surface properties, Virtual reality}, url = {http://dx.doi.org/10.1109/TMECH.2004.828625}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/44-09tmech02omalley-print.pdf}, author = {O{\textquoteright}Malley, M.K. and Michael Goldfarb} } @proceedings {04448428417, title = {Virtual labs in the engineering curriculum}, year = {2004}, note = {Engineering curriculum;Real-time parametric changes;Graphical interfaces;Virtual labs;
}, pages = {15293 - 15304}, address = {Salt Lake City, UT, United States}, abstract = {Computer simulations have been developed for use as student exercises to illustrate concepts required for various engineering courses. These simulations or Virtual Labs are highly graphical and interactive to help undergraduate students understand basic concepts by graphically solving problems and by visualization of real-time parametric changes. These Virtual Labs (or VL{\textquoteright}s) can be used productively in conjunction with existing laboratory experiments as pre-lab exercises, but the more important benefit is realized in cases of concepts that have no experimental support and in courses that traditionally do not have an associated laboratory course. These VL{\textquoteright}s are generated in the software package Lab VIEW, which offers graphical interfaces for the student and can be formatted as standalone files, which the students can download and access at their convenience, without the need for Lab VIEW software. Currently five VL{\textquoteright}s have been generated and several have been evaluated by students in appropriate classes.
}, keywords = {Computer programming languages, Computer simulation, Curricula, Data reduction, Graphic methods, Students, Visualization}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/mcstravick2004asee.pdf}, author = {David M. McStravick and O{\textquoteright}Malley, M.K.} } @proceedings {1869, title = {Current challenges in the control of haptic interfaces and bilateral teleoperation systems}, year = {2003}, pages = {743-750}, publisher = {American Society of Mechanical Engineers}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/speich2003asme.pdf}, author = {Speich, John E and O{\textquoteright}Malley, Marcia K} } @article {03507772035, title = {Haptic feedback applications for robonaut}, journal = {Industrial Robot}, volume = {30}, number = {6}, year = {2003}, note = {Haptic feedback;Humanoid robot;Teleoperator;}, pages = {531 - 542}, abstract = {Robonaut is a humanoid robot designed by the Robotic Systems Technology Branch at NASA{\textquoteright}s Johnson Space Center in a collaborative effort with Defense Advanced Research Projects Agency. This paper describes the implementation of haptic feedback into Robonaut and Robosim, the computer simulation of Robotonaut. In the first experiment, we measured the effects of varying feedback to a teleoperator during a handrail grasp task. Second, we conducted a teleoperated task, inserting a flexible beam into an instrumented receptable. In the third experiment, we used Robonaut to perform a two-arm task where a compliant ball was translated in the robot{\textquoteright}s workspace. The experimental results are encouraging as the Dexterous Robotics Lab continues to implement force feedback into its teleoperator hardware architecture.
}, keywords = {Computer control systems, Feedback control, Haptic interfaces, Robotics, Space applications, Telecontrol equipment}, url = {http://dx.doi.org/10.1108/01439910310506800}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/IndustrialRobotO\%27Malley-Ambrose2003.pdf}, author = {O{\textquoteright}Malley, M.K. and Robert O. Ambrose} } @proceedings {7780496, title = {Passive and active assistance for human performance of a simulated underactuated dynamic task}, year = {2003}, note = {simulated underactuated dynamic task;machine-mediated training;virtual fixtures;active assist;haptic feedback;visual feedback;
}, pages = {348 - 55}, address = {Los Angeles, CA, USA}, abstract = {Machine-mediated training of dynamic task completion is typically implemented with passive intervention via virtual fixtures or active assist by means of record and replay strategies. During interaction with a real dynamic system however, the user relies on both visual and haptic feedback real-time in order to elicit desired motions. This work investigates human performance in a Fitts{\textquoteright} type targeting task with an underactuated dynamic system. Performance, in terms of number of hits and between-target tap times, is measured while various passive and active control modes are displayed concurrently with the haptic feedback from the simulated system{\textquoteright}s own dynamic behavior. It Is hypothesized that passive and active assist modes that are implemented during manipulation of simulated underactuated systems could be beneficial in rehabilitation applications. Results indicate that human performance can be improved significantly with the passive and active assist modes
}, keywords = {Haptic interfaces, Virtual reality}, url = {http://dx.doi.org/10.1109/HAPTIC.2003.1191308}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/omalley2003HAPTICS.pdf}, author = {O{\textquoteright}Malley, M.K. and Abhishek Gupta} } @proceedings {1191334, title = {Simplified authoring of 3D haptic content for the World Wide Web}, year = {2003}, month = {03/2003}, pages = {428-429}, keywords = {authoring systems, Haptic interface, Internet, Internet browser, modeling language, programming, scripting, three-dimensional content, three-dimensional haptic scenes, virtual reality languages 3D haptic content authoring, VRML, Web page}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/161-getPDF.pdf}, author = {O{\textquoteright}Malley, M.K. and Shannon Hughes} } @proceedings {70, title = {Simulated Bilateral Teleoperation of Robonaut}, year = {2003}, address = {Long Beach, CA}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/70-PV2003_6272.pdf}, author = {O{\textquoteright}Malley, M.K. and Kelsey J. Hughes and D. F. Magruder and Robert O. Ambrose} } @proceedings {7971173, title = {Skill transfer in a simulated underactuated dynamic task}, year = {2003}, note = {underactuated dynamic system;Fitts{\textquoteright} type;skill transfer;haptic feedback;
}, pages = {315 - 20}, address = {Millbrae, CA, USA}, abstract = {Machine-mediated teaching of dynamic task completion is typically implemented with passive intervention via virtual fixtures or active assist by means of record and replay strategies. During interaction with a real dynamic system however, the user relies on both visual and haptic feedback in order to elicit desired motions. This work investigates skill transfer from assisted to unassisted modes for a Fitts{\textquoteright} type targeting task with an underactuated dynamic system. Performance, in terms of between target tap times, is measured during an unassisted baseline session and during various types of assisted training sessions. It is hypothesized that passive and active assist modes that are implemented during training of a dynamic task could improve skill transfer to a real environment or unassisted simulation of the task. Results indicate that transfer of skill is slight but significant for the assisted training modes
}, keywords = {computer based training, Haptic interfaces, learning (artificial intelligence), Virtual reality}, url = {http://dx.doi.org/10.1109/ROMAN.2003.1251864}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/omalley2003ieeeskilltrans.pdf}, author = {O{\textquoteright}Malley, M.K. and Abhishek Gupta} } @article {02427145860, title = {The effect of force saturation on the haptic perception of detail}, journal = {IEEE/ASME Transactions on Mechatronics}, volume = {7}, number = {3}, year = {2002}, note = {Force saturation effect;Haptic perception;Force feedback;}, pages = {280 - 288}, abstract = {This paper presents a quantitative study of the effects of maximum capable force magnitude of a haptic interface on the haptic perception of detail. Specifically, the haptic perception of detail is characterized by identification, detection, and discrimination of round and square cross-section ridges, in addition to corner detection tests. Test results indicate that performance, measured as a percent correct score in the perception experiments, improves in a nonlinear fashion as the maximum allowable level of force in the simulation increases. Further, all test subjects appeared to reach a limit in their perception capabilities at maximum-force output levels of 3-4 N, while the hardware was capable of 10 N of maximum continuous force output. These results indicate that haptic interface hardware may be able to convey sufficient perceptual information to the user with relatively low levels of force feedback. The data is compiled to aid those who wish to design a stylus-type haptic interface to meet certain requirements for the display of physical detail within a haptic simulation.
}, keywords = {Computer control systems, Computer simulation, Feedback control, Haptic interfaces, Identification (control systems), Nonlinear control systems, Virtual reality}, url = {http://dx.doi.org/10.1109/TMECH.2002.802725}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/omalley2002ieee.pdf}, author = {O{\textquoteright}Malley, M.K. and Michael Goldfarb} } @proceedings {7379354, title = {The implications of surface stiffness for size identification and perceived surface hardness in haptic interfaces}, volume = {vol.2}, year = {2002}, note = {surface stiffness;virtual surface stiffness;haptic perception;time delays;size identification;perceived surface hardness;haptic interfaces;
}, pages = {1255 - 60}, address = {Washington, DC, USA}, abstract = {This paper presents a two-part study of the effects of virtual surface stiffness on haptic perception. First, size identification experiments were performed to determine the effects of system quality, in terms of surface stiffness, on the ability of a human to identify square cross-section ridges by size in a simulated environment. Then, discrimination experiments were performed to determine relationships between virtual surface stiffness and simulation quality in terms of perceived surface hardness. Results of experiments to test human haptic perception for varying virtual surface stiffnesses indicate that haptic interface hardware may be able to convey sufficient perceptual information to the user at relatively low levels of virtual surface stiffness. Subjects, however, can perceive improvements in perceived simulated surface hardness as stiffness levels are increased in the range of achievable parameters for this hardware. The authors draw several conclusions about the allowable time delays in a haptic interface system based on the results of the surface stiffness experiments
}, keywords = {delays, Haptic interfaces, human factors, Virtual reality}, url = {http://dx.doi.org/10.1109/ROBOT.2002.1014715}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/omalley2002ieeesurfacestiffness.pdf}, author = {O{\textquoteright}Malley, M.K. and Michael Goldfarb} }