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About

Chaoyang Chen is a leading researcher at the intersection of biomedical engineering, rehabilitation robotics, and artificial intelligence. His work focuses on decoding human motor intent from bioelectrical signals—primarily electromyography (EMG) and electroencephalography (EEG)—to enable intuitive, volitional control of assistive devices such as upper-limb exoskeletons and prosthetic hands. A key contribution is his integration of machine learning and deep learning algorithms to overcome challenges like signal noise and individual variability, achieving robust hand motion pattern recognition. His 2023 study on volitional control of an upper-limb exoskeleton (23 citations) and his 2020 work on EMG-based hand motion recognition (15 citations) are foundational in this field. Chen has also applied predictive machine learning to clinical orthopedics, developing models to forecast blood transfusion needs in total knee arthroplasty (16 citations). Additionally, his deep learning frameworks for decoding movement intention from EEG in patients with spinal cord injury (6 citations) represent a critical step toward brain-controlled prosthetics. With a growing citation record and a clear translational focus, Chen’s research is shaping the future of intelligent, human-centered rehabilitation technology.