Anyuan Zhang

Changchun University of Science and Technology

Papers

Total Citations

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About

Anyuan Zhang is a leading researcher in biomedical signal processing and human–machine interaction, with a core focus on electromyography (EMG) pattern recognition for rehabilitation robotics and prosthetics. Zhang’s most impactful work addresses a critical barrier to clinical adoption: the degradation of EMG classification accuracy over repeated uses caused by electrode shifting. In a highly cited 2021 study (30 citations), Zhang pioneered a method that combines feature selection with incremental transfer learning, enabling models to adapt to changing data distributions without requiring full retraining. This innovation significantly improves the robustness and practicality of myoelectric control systems, bringing them closer to reliable, long-term deployment in assistive devices. By tackling the real-world challenge of signal variability, Zhang’s contributions directly enhance the usability of prostheses and rehabilitation robots for patients. With a growing citation record and a focus on translational impact, Anyuan Zhang is recognized for bridging the gap between advanced machine learning techniques and tangible improvements in assistive technology, making them a key figure in the evolution of intelligent, adaptive human–machine interfaces.