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IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society|May 11, 2026
Forecasting Dropout in Home-Based Movement Rehabilitation after Stroke with Sensors and Machine LearningSangjoon J Kim, George H Collier, Jacob Cartwright, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 19, 2012
Supinator Extender (SUE): a pneumatically actuated robot for forearm/wrist rehabilitation after strokeJames Allington, Steven J Spencer, Julius Klein, et al.
IEEE ... International Conference on Rehabilitation Robotics : [Proceedings]|August 18, 2017
Wearable sensing for rehabilitation after stroke: Bimanual jerk asymmetry encodes unique information about the variability of upper extremity recoveryDiogo S de Lucena, Oliver Stoller, Justin B Rowe, et al.
Disability and Rehabilitation. Assistive Technology|June 29, 2019
Bimanual wheelchair propulsion by people with severe hemiparesis after strokeBrendan W Smith, Diana R Bueno, Daniel K Zondervan, et al.
Journal of Neurotrauma|September 29, 2015
Robotic Rehabilitator of the Rodent Upper Extremity: A System and Method for Assessing and Training Forelimb Force Production after Neurological InjuryKelli G Sharp, Jaime E Duarte, Berkenesh Gebrekristos, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society|April 20, 2020
Feasibility of Wearable Sensing for In-Home Finger Rehabilitation Early After StrokeQuentin Sanders, Vicky Chan, Renee Augsburger, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 9, 2015
The variable relationship between arm and hand use: a rationale for using finger magnetometry to complement wrist accelerometry when measuring daily use of the upper extremityJustin B Rowe, Nizan Friedman, Vicky Chan, et al.
Neural Computation|October 28, 2003
Modeling reaching impairment after stroke using a population vector model of movement control that incorporates neural firing-rate variabilityDavid J Reinkensmeyer, Mario G Iobbi, Leonard E Kahn, et al.
Experimental Brain Research|August 23, 2018
Neural circuits activated by error amplification and haptic guidance training techniques during performance of a timing-based motor task by healthy individualsMarie-Hélène Milot, Laura Marchal-Crespo, Louis-David Beaulieu, et al.
Frontiers in Rehabilitation Sciences|July 5, 2023
Exercise repetition rate measured with simple sensors at home can be used to estimate Upper Extremity Fugl-Meyer score after strokeVeronica A Swanson, Christopher A Johnson, Daniel K Zondervan, et al.
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