@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 {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.} } @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.} } @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} } @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} } @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 {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 {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 {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} } @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 {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 {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 {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 {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} } @proceedings {1823, title = {Characterization of Surface Electromyography Patterns of Healthy and Incomplete Spinal Cord Injury Subjects Interacting with an Upper-Extremity Exoskeleton}, year = {2017}, month = {07/2017}, publisher = {IEEE}, address = {London, UK}, 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 {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 {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 {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} } @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.} } @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} } @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 {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 {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.} } @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} } @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 {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} } @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} } @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 {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 {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.} }