Stroke Rehabilitation Robotics

Research Description

Alongside human neuromusculoskeletal models, we have developed dynamic models and optimal controllers for upper-limb stroke rehabilitation robotic systems, which provide assistive/resistive loads according to patient-specific needs. We are now gamifying the robotic system to enhance patient experience and are using artificial intelligence to learn patient-specific characteristics. The stroke rehabilitation robotic system is currently being tested at Grand River Hospital.

Student Researchers 

Arash Hashemi
Parya Khoshroo
Reza Sharif Razavian (Alumnus)
Borna Ghannadi (Alumnus)

Keywords and Themes

• Stroke Rehabiliation 
• Physical Human-Robot Interaction 
• Biomechatronic Systems Modelling and Control
• Rehabiliation Robotics 
• Upper-Limb Musculoskeletal Modelling 

     Stroke_1 Stroke_2

Related Publications 

• Ghannadi B, Razavian RS, and McPhee J. (2018). Configuration-Dependent Optimal Impedance Control of an Upper Extremity Stroke Rehabilitation Manipulandum. Frontiers in Robotics and AI. DOI: 10.3389/frobt.2018.00124.
• Ghannadi B, Mehrabi N, Razavian RS, and McPhee J. (2017). Nonlinear Model Predictive Control of an Upper Extremity Rehabilitation Robot using a Two-Dimensional Human-Robot Interaction Model. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). DOI: 10.1109/IROS.2017.8202200.
• Ghannadi B and McPhee J. (2015). Optimal Impedance Control of an Upper Limb Stroke Rehabilitation Robot. ASME 2015 Dynamic Systems and Control Conference. DOI: 10.1115/DSCC2015-9689.