Chengfei Zheng

Huazhong University of Science and Technology

Papers

Total Citations

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About

Chengfei Zheng’s research lies at the intersection of human–machine interfaces, biomechatronics, and intuitive robotic control, with a primary focus on decoding human motion intent from surface electromyography (EMG) signals. His work addresses a critical challenge in human-centered robotics: translating complex, multi-degree-of-freedom (DoF) arm movements—such as coordinated shoulder and elbow motions—into seamless, natural control commands. In his most cited paper (2015, 10 citations), Zheng developed an EMG-based method to continuously estimate shoulder and elbow joint angles, enabling more fluid and intuitive myoelectric control for prosthetic and assistive devices. A related study (2015, 3 citations) advanced motion classification for 3-D arm movements involving multiple DoFs, further refining pattern recognition techniques to interpret muscle activity into precise motion intentions. These contributions have helped bridge the gap between raw biological signals and practical robotic interfaces, offering pathways toward more responsive and user-friendly prosthetics and exoskeletons. Zheng’s work is particularly valuable for researchers and engineers developing next-generation human–machine systems that demand both accuracy and naturalness of control.