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About

Jirou Feng is a leading researcher at the intersection of neural engineering and wearable robotics, specializing in human-robot interaction through biosignal processing. Their work focuses on decoding human motion intention using surface electromyography (sEMG) and electroencephalography (EEG) to enable intuitive control of exoskeletons and rehabilitation devices. Feng’s most impactful contribution, "Recognition of walking environments and gait period by surface electromyography" (70 citations), addresses the critical challenge of predicting wearer movement for lower-limb exoskeletons, demonstrating how multi-sensor fusion can enhance human-machine synergy. Their 2022 study on sEMG characteristics for motion intention recognition (42 citations) further systematizes these approaches, while their work on EEG-EMG hybrid systems for hand rehabilitation in chronic stroke patients (9 citations) pioneers brain-body interfaces for restoring motor function. Feng has also advanced sensor technology, designing flexible high-density sEMG sensors that improve signal fidelity and reduce positional sensitivity. By tackling implementation issues in EMG-based detection and integrating vision-based grasping in teleoperation, Feng bridges fundamental neurophysiology with practical robotic applications, making assistive technologies more responsive and accessible for individuals with motor impairments.