Huiqun Fu
Papers
2
Total Citations
22
H-Index
2
About
Huiqun Fu is a researcher focused on advancing rehabilitation robotics through the integration of biosignal processing and human-machine interaction. Her primary research areas include surface electromyography (sEMG)-based motion pattern recognition, upper limb rehabilitation robotics, and intelligent control systems for assistive technologies. Fu’s major contributions center on developing methods to decode complex shoulder-elbow composite motions from sEMG signals, enabling more natural and adaptive control of rehabilitation robots for hemiplegic patients. Her most cited works, including “sEMG-based shoulder-elbow composite motion pattern recognition and control methods for upper limb rehabilitation robot” (2018, 11 citations) and “The design of a hemiplegic upper limb rehabilitation training system based on surface EMG signals” (2018, 11 citations), demonstrate innovative approaches that fuse autoregressive model coefficients with wavelet features to improve pattern recognition accuracy. These systems allow both single-degree and multi-degree-of-freedom training, bridging the gap between robotic assistance and patient intent. Fu’s work has meaningful implications for restoring motor function in stroke survivors, contributing to the growing field of intelligent, patient-centered rehabilitation technology.
Research Focus
Key Achievements
Top Papers
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- 2