Papers
3
Total Citations
12
H-Index
2
About
Zhouyang Chen is a researcher at the intersection of rehabilitation robotics, autonomous navigation, and human–robot interaction. His work spans two critical domains: restoring motor function in stroke patients and advancing robotic autonomy in complex environments. Chen’s most impactful contribution is a 2024 systematic review and meta-analysis on upper limb robot-assisted training for stroke rehabilitation, which synthesized evidence from multiple clinical trials to assess improvements in motor function, daily living activities, and muscle tone—a study that has already garnered 7 citations. In parallel, he has tackled path planning challenges for McNum wheel robots by fusing RRT* with artificial potential field methods to avoid local minima, and developed a novel human–robot skill transfer framework using inverse velocity admittance control for soft tissue cutting tasks, such as automated sheep hindquarter processing. His work on the latter, published in 2024, demonstrates how multi-demonstration learning can generalize cutting strategies to complex 3D anatomy. Chen’s research bridges the gap between assistive medical robotics and industrial automation, with his meta-analysis providing crucial evidence for clinical adoption of upper limb robots.
Research Focus
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Top Papers
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