Papers
2
Total Citations
11
H-Index
2
About
Bingquan Shen has made impactful contributions to rehabilitation robotics, with a primary focus on developing wearable assistive devices for stroke patients. His research centers on lower extremity rehabilitation technology, particularly the integration of surface electromyography (EMG) signals for intuitive human-machine interaction. In his most cited work (2013, 9 citations), Shen introduced a novel wearable robotic device that detects user intention through EMG signals to provide precise assistive torque during rehabilitation, enabling more natural and effective therapy for patients in early or severe stages of recovery. He further advanced this line of research by developing a Function Approximation Technique (FAT)-based adaptive control system (2013, 2 citations) for the same anthropomorphic lower extremity device, which actuates hip and knee joints in the sagittal plane. This control approach allows the robot to adapt to individual patient needs without requiring complex dynamic models, significantly improving safety and comfort during therapy. Shen's work bridges the gap between advanced control theory and practical clinical application, demonstrating how intelligent robotic systems can enhance neurorehabilitation outcomes for stroke survivors.
Research Focus
Key Achievements
Top Papers
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