@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 {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 {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} } @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} } @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 {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} } @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 {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} } @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 {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 {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} } @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 {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 {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} } @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} } @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 {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 {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 {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 {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.} } @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 {1817, title = {Maintaining Subject Engagement during Robotic Rehabilitation with a Minimal Assist-as-Needed (mAAN) Controller}, year = {2017}, month = {07/2017}, publisher = {IEEE}, address = {London, UK}, abstract = {

One challenge of robotic rehabilitation interventions is devising ways to encourage and maintain high levels of subject involvement over long duration therapy sessions. Assist-as-needed controllers have been proposed which modulate robot intervention in movements based on measurements of subject involvement. This paper presents a minimal assist-as-needed controller, which modulates allowable error bounds and robot intervention based on sensorless force measurement accomplished through a nonlinear disturbance observer. While similar algorithms have been validated using healthy subjects, this paper presents a validation of the proposed mAAN control algorithm{\textquoteright}s ability to encourage user involvement with an impaired individual. User involvement is inferred from muscle activation, measured via surface electromyography (EMG). Experimental validation shows increased EMG muscle activation when using the proposed mAAN algorithm compared to non-adaptive algorithms.

}, issn = {978-1-5386-2296-4}, doi = {10.1109/ICORR.2017.8009222}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Pehlivan_2017_Maintaining.pdf}, author = {Ali Utku Pehlivan and Dylan P. Losey and Rose, Chad G.} } @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 {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} } @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 {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} } @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 {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} } @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.} } @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.} } @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 {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} } @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 {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 {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 {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} } @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 {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.} } @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} } @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} } @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.} }