@conference {497, title = {Dynamic Finger Task Identification Using Electromyography}, booktitle = {IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)}, year = {2022}, author = {Paria Esmatloo and Keya Ghonasgi and Raymond King and Ashish D. Deshpande} } @article {499, title = {Human-Like Endtip Stiffness Modulation Inspires Dexterous Manipulation With Robotic Hands}, journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering}, volume = {30}, year = {2022}, author = {Anna Shafer and Ashish D. Deshpande} } @conference {498, title = {Human-Robot Interaction: Muscle Activation and Angular Location Affect Soft Tissue Stiffness}, booktitle = {IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)}, year = {2022}, author = {Saad N. Yousaf and Keya Ghonasgi and Paria Esmatloo and Ashish D. Deshpande} } @conference {496, title = {Impact of Gravity Compensation on Upper Extremity Movements in Harmony Exoskeleton}, booktitle = {International Conference on Rehabilitation Robotics (ICORR)}, year = {2022}, author = {Rhet O. Hailey and Ana C. de Oliveira and Keya Ghonasgi and R. Whitford and R. Lee and Chad G. Rose and Ashish D. Deshpande} } @article {495, title = {Novel Biomedical Technologies: Rehabilitation Robotics}, journal = {Current Opinion in Biomedical Engineering}, volume = {22}, year = {2022}, author = {Ashish D. Deshpande} } @conference {467, title = {An Actuated Indenter for Characterization of Soft Tissue Towards Human-Centered Design}, booktitle = { IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)}, year = {2021}, author = {Saad N. Yousaf and Keya Ghonasgi and Paria Esmatloo and Ashish D. Deshpande} } @article {460, title = {Assessment of Upper-extremity Joint Angles using Harmony Exoskeleton}, journal = { IEEE Transactions on Neural Systems and Rehabilitation Engineering}, year = {2021}, issn = {1558-0210}, author = {Ana C. de Oliveira and James S. Sulzer and Ashish D. Deshpande} } @article {452, title = {Balancing Stability and Stiffness Through the Optimization of Parallel Compliance: Using Coupled Tendon Routing}, journal = {IEEE Robotics \& Automation Magazine}, volume = {28}, year = {2021}, month = {06/2021}, pages = {14-22}, author = {Mincheol Kim and Ashish D. Deshpande} } @conference {469, title = {Is the Cerebellum a Model-Based Reinforcement Learning Agent?}, booktitle = {Adaptive and Learning Agents (ALA) Workshop at the International Conference on Autonomous Agents and Multiagent Systems}, year = {2021}, author = {Bharath Masetty and Reuth Mirsky and Ashish D. Deshpande and Michael Mauk and Peter Stone} } @conference {465, title = {Design and Validation of a Novel Exoskeleton Hand Interface: The Eminence Grip}, booktitle = {IEEE International Conference on Robotics and Automation (ICRA)}, year = {2021}, author = {Keya Ghonasgi and Chad G. Rose and Ana C. de Oliveira and Rohit J. Varghese and Ashish D. Deshpande} } @article {448, title = {Improvement of Hand Functions of SCI Patients with EMG-driven Hand Exoskeleton: a Feasibility Study}, journal = {Wearable Technologies}, year = {2021}, abstract = {

We have developed a one-of-a-kind hand exoskeleton, called Maestro, which can power finger movements of those surviving severe disabilities to complete daily tasks using compliant joints. In this paper, we present results from a practical EMG control strategy conducted with spinal cord injury (SCI) patients (C5, C6 and C7) in which the subjects completed daily tasks controlling Maestro with electromyography (EMG) signals from their forearm muscles. With its compliant actuation and its degrees of freedom (DOF) that match the natural finger movements, Maestro is capable of helping the subjects grasp and manipulate a variety of daily objects (more than 15 from a standardized set). To generate control commands for Maestro, an artificial neural network algorithm was implemented along with a probabilistic control approach to classify and deliver four hand poses robustly with three EMG signals measured from the forearm and palm. Increase in the scores of a standardized test, called the Sollerman hand function test (SHFT), and enhancement in different aspects of grasping such as strength shows feasibility that Maestro can be capable of improving the hand function of SCI subjects.

}, author = {Youngmok Yun and Youngjin Na and Paria Esmatloo and Sarah Dancausse and Alfredo Serrato and Curtis A. Merring and Priyanshu Agarwal and Ashish D. Deshpande} } @article {453, title = {Kinematic comparison of single degree-of-freedom robotic gait trainers}, journal = {Mechanism and Machine Theory}, year = {2021}, abstract = {

Single degree-of-freedom mechanized gait trainers employing linkage mechanisms
can imitate the gait trajectory of the human user at a potentially lower cost than current
commercial solutions. Our goal was to evaluate recently introduced four-, six- and
eight-bar designs from the standpoint of kinematics, that is, the ability to follow a
natural gait pattern. Based on gait database of 113 healthy individuals, we synthesized
mechanisms allowing two link length adjustments and compared trajectory and path

accuracy of the ankle across mechanisms. We used cross-validation to obtain data-
independent accuracy. We used gait trajectories from a large human database and

predicted additional trajectories to represent effects of varying heights and speeds. We
found that trajectory error was significantly lower in the eight-bar mechanism (3.77 {\textpm}
0.17 cm, mean {\textpm} SD) than the four- (6.84 {\textpm} 0.37 cm) and six-bar (7.15 {\textpm} 0.48 cm)

configurations (p\<0.0001). However, we did not observe differences in time-
independent path error between configurations, or in mechanical advantage (p\>0.05).

We conclude that the eight-bar configuration is best when the mechanism is tied to a
constant velocity actuator, whereas the four-bar mechanism performs as well if the
actuator is well-controlled.

}, author = {Jeonghwan Lee and Lailu Li and Sung Yul Shin and Ashish D. Deshpande and James Sulzer} } @conference {466, title = {A Method for the Analysis of Physical Human Robot Interaction}, booktitle = { IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)}, year = {2021}, author = {Saad N. Yousaf and Paria Esmatloo and Keya Ghonasgi and Ashish D. Deshpande} } @article {455, title = {A Modular Design for Distributed Measurement of Human-Robot Interaction Forces in Wearable Devices}, journal = {Sensors}, year = {2021}, author = {Keya Ghonasgi and Saad N. Yousaf and Paria Esmatloo and Ashish D. Deshpande} } @conference {464, title = {Monitoring Fatigue-Induced Changes in Performance during Robot-Mediated Dynamic Movement}, booktitle = {IEEE International Conference on Robotics and Automation (ICRA)}, year = {2021}, author = {Kaci E. Madden and Dragan Djurdjanovic and Ashish D. Deshpande} } @article {470, title = {The Road Forward for Upper Extremity Rehabilitation Robotics}, journal = {Current Opinion in Biomedical Engineering}, year = {2021}, abstract = {

Despite concerted efforts over the last three decades, upper-extremity robotic rehabilitation has yet to reach its full potential. We assert that assuming the goal of robotic rehabilitation is to automate conventional therapy may have led to overly narrow research directions and to mixed results from clinical studies. Recontextualizing this assumption opens promising research avenues for roboticists. Breaking the robotic device design loop and instead seeking out {\textquoteleft}big data{\textquoteright} opportunities has the potential to identify promising robot-mediated interventions. This will require a shift in roboticists{\textquoteright} attitudes towards participating in neuroscience and clinical research. By expanding assessment beyond kinematics, robotic devices can provide clinicians with a more complete picture of impairment and recovery. We discuss the current assumptions in greater detail, and point towards promising research in these revised directions.

}, issn = {ISSN 2468-4511}, author = {Chad G. Rose and Ashish D. Deshpande and Jacob Carducci and Jeremy D.Brown} } @conference {449, title = {Design and Validation of a Sensorized Physical Human-Robot Interface for Distributed Force Measurement}, booktitle = {2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Workshop on Ergonomic Human-Robot Collaboration: Opportunities and Challenges}, year = {2020}, author = {Keya Ghonasgi and Saad N. Yousaf and Paria Esmatloo and Ruth Heckler and Job Ramirez and Chad G. Rose and Ashish D. Deshpande} } @conference {428, title = {Fingertip Position and Force Control for Dexterous Manipulation through Model-Based Control of Hand-Exoskeleton-Environment}, booktitle = {IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM) (AIM 2020). }, year = {2020}, author = {Paria Esmatloo and Ashish D. Deshpande} } @conference {427, title = {Human-like Endtip Stiffness Modulation for Stable, Dexterous Manipulation}, booktitle = {8th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob 2020)}, year = {2020}, author = {Anna Shafer and Ashish D. Deshpande} } @proceedings {432, title = {A Novel Inverse Kinematics Method for Upper-Limb Exoskeleton under Joint Coordination Constraints}, year = {2020}, author = {Stefano D. Gasperina and Keya Ghonasgi and Ana C. de Oliveira and Ashish D. Deshpande} } @conference {411, title = {Estimating the Effect of Robotic Intervention on Elbow Joint Motion}, booktitle = { IEEE International Symposium on Robot and Human Interactive Communication }, year = {2019}, month = {09/2019}, author = {Keya Ghonasgi and Ana C. de Oliveira and Anna Shafer and Chad G. Rose and Ashish D. Deshpande} } @article {395, title = {A Framework for Adaptation of Training Task, Assistance and Feedback for Optimizing Motor (Re)-Learning With a Robotic Exoskeleton}, journal = {IEEE Robotics and Automation Letters}, volume = {4}, year = {2019}, chapter = {808}, author = {Priyanshu Agarwal and Ashish D. Deshpande} } @article {379, title = {Assessing Wrist Movement with Robotic Devices}, journal = {IEEE Transactions on Neural Systems \& Rehabilitation Engineering}, year = {2018}, author = {Chad G. Rose and Evan Pezent and Claudia K. Kanny and Ashish D. Deshpande and Marcia K. O{\textquoteright}Malley} } @conference {371, title = {Human-Inspired Object Manipulation Control with the Anatomically Correct Testbed Hand}, booktitle = {IEEE International Conference on Robotics and Automation}, year = {2018}, author = {Taylor D. Niehues and Ashish D. Deshpande} } @conference {316, title = {Analyzing Achievable Stiffness Control Bounds of Robotic Hands With Compliantly Coupled Finger Joints}, booktitle = {IEEE International Conference on Robotics and Automation (ICRA)}, year = {2017}, author = {Prashant Rao and Gray C. Thomas and Luis Sentis and Ashish D. Deshpande} } @article {300, title = {Design, Control and Testing of a Thumb Exoskeleton with Series Elastic Actuation}, journal = {International Journal of Robotics Research}, year = {2017}, keywords = {Exoskeleton, Hand, Thumb}, author = {Priyanshu Agarwal and Youngmok Yun and Jonas Fox and Kaci E. Madden and Ashish D. Deshpande} } @conference {319, title = {An EMG-Driven Assistive Hand Exoskeleton for Spinal Cord Injury Patients: Maestro}, booktitle = {IEEE International Conference on Robotics and Automation (ICRA)}, year = {2017}, author = {Youngmok Yun and Sarah Dancausse and Paria Esmatloo and Alfredo Serrato and Curtis A. Merring and Ashish D. Deshpande} } @conference {334, title = {Methodologies for determining minimal grasping requirements and sensor locations for sEMG-based assistive hand orthosis for SCI patients}, booktitle = {IEEE International Conference of Rehabilitation Robotics (ICORR)}, year = {2017}, author = {Youngmok Yun and Paria Esmatloo and Alfredo Serrato and Curtis A. Merring and Ashish D. Deshpande} } @article {331, title = {Series Elastic Actuators for Small-Scale Robotic Applications}, journal = {Journal of Mechanisms and Robotics}, volume = {9}, year = {2017}, month = {03/2017}, chapter = {1168}, author = {Priyanshu Agarwal and Ashish D. Deshpande} } @article {332, title = {An Upper-Body Rehabilitation Exoskeleton Harmony with an Anatomical Shoulder Mechanism: Design, Modeling, Control, and Performance Evaluation}, journal = {International Journal of Robotics Research (IJRR)}, volume = {36}, year = {2017}, pages = {414-435}, author = {Bongsu Kim and Ashish D. Deshpande} } @conference {325, title = {BloomBot, a Creative and Autonomous Land Art Robot}, booktitle = {IEEE International Conference on Robotics and Automation (IROS)}, year = {2016}, author = {James Sham and Mark L. Jennings and Ashish D. Deshpande} } @conference {315, title = {Crocheted Artificial Tendons and Ligaments for the Anatomically Correct Testbed (ACT) Hand}, booktitle = {IEEE ROBIO}, year = {2015}, author = {Z. Xu and Y. Matsuoka and Ashish D. Deshpande} } @conference {317, title = {Effect of Parallel Compliance on Stability of Robotic Hands With Series Elastic Actuators}, booktitle = {ASME Dynamic Systems and Controls Conference (DSCC)}, year = {2015}, month = {10/2015}, author = {Prashant Rao and Taylor D. Niehues and Ashish D. Deshpande} }