Zhuochen Fan
Papers
1
Total Citations
23
H-Index
1
About
Zhuochen Fan is a researcher whose work bridges biomedical signal processing and human movement analysis, with a particular focus on electromyography (EMG) and gait dynamics. His most cited study, "Research on EMG segmentation algorithm and walking analysis based on signal envelope and integral electrical signal" (2018), has garnered 23 citations, establishing a foundation for non-invasive muscle activity assessment during locomotion. Fan’s key contributions lie in developing robust segmentation algorithms that extract meaningful features from raw EMG data—specifically through signal envelope and integral electrical signal analysis—enabling more accurate classification of gait phases and muscle activation patterns. This work holds significant implications for rehabilitation engineering, prosthetics control, and sports biomechanics, offering a practical framework for decoding neuromuscular intent. By refining how researchers parse complex electrophysiological signals, Fan has advanced the precision of wearable sensor applications and real-time biofeedback systems. His research continues to influence studies on human motor control, making him a notable figure in the intersection of signal processing and clinical movement science.
Research Focus
Key Achievements
Top Papers
- 1