Research Description
In addition to human neuromusculoskeletal models, we have developed dynamic models and optimal controllers for upper-limb stroke rehabilitation robotics, 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 robotÌýis currently being tested at .
Student ResearchersÌý
•ÌýAli NasrÌý(´¡±ô³Ü³¾²Ô³Ü²õ)
• Jason HunterÌý(´¡±ô³Ü³¾²Ô³Ü²õ)
​â¶Ä‹â¶Ä‹â¶Ä‹â¶Ä‹â¶Ä‹â¶Ä‹â€¢ Arash HashemiÌý(´¡±ô³Ü³¾²Ô³Ü²õ)​â¶Ä‹â¶Ä‹â¶Ä‹â¶Ä‹â¶Ä‹â¶Ä‹
• Parya KhoshrooÌý(´¡±ô³Ü³¾²Ô³Ü²õ)
• Reza Sharif RazavianÌý(´¡±ô³Ü³¾²Ô³Ü²õ)
• Borna GhannadiÌý(´¡±ô³Ü³¾²Ô³Ü²õ)
Keywords and Themes
•ÌýStroke RehabiliationÌý
• Physical Human-Robot InteractionÌý
•ÌýBiomechatronic Systems Modelling and Control
• Rehabiliation RoboticsÌý
• Upper-Limb Musculoskeletal ModellingÌý
Related PublicationsÌý
• 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.
•ÌýGhannadi 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.
•ÌýGhannadi 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.