Xiabing Zhang

University of Electronic Science and Technology of China, Chengdu University of Traditional Chinese Medicine

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About

Xiabing Zhang is a rising leader in neural engineering and rehabilitation robotics, whose work bridges the gap between human physiology and intelligent machines. Her research centers on decoding complex motor intent from electromyography (EMG) and electroencephalography (EEG) signals to drive next-generation wearable exoskeletons and prosthetics. A key contribution is the development of a wearable master–slave rehabilitation robot integrating an epidermal array electrode sleeve with a multichannel EMG network, enabling precise, non-invasive control for stroke recovery (15 citations). Zhang further advanced the field by fusing EEG and EMG data through Granger causality analysis to map central–peripheral nervous system activation during exoskeleton-assisted movement (6 citations). Her most recent work introduces a hybrid CNN-Transformer architecture that achieves continuous, fine-grained finger motion decoding from surface EMG, outperforming traditional methods in dexterity and robustness (4 citations). By combining deep learning with physiological signal processing, Zhang is pioneering more intuitive and adaptive human–machine interfaces, with direct applications in assistive technology and neurorehabilitation.