Wuxiang Shi
Papers
2
Total Citations
76
H-Index
2
About
Wuxiang Shi is a leading researcher in biomechatronics and intelligent human-robot interaction, with a primary focus on predictive modeling of human lower extremity dynamics. His work bridges artificial intelligence and biomechanics to advance rehabilitation engineering and exoskeleton control. Shi’s most influential contribution is his 2019 study on intelligent prediction of human lower extremity joint moments using artificial neural networks, which has garnered 58 citations. This work addresses a critical challenge: enabling accurate joint moment estimation without relying on specialized kinetic measurement equipment, thereby making rehabilitation assessment more accessible and practical for real-world applications. In a subsequent 2020 study (18 citations), Shi advanced the field by developing a systematic method to determine online measurable input variables for neural network models, grounded in the Hill muscle model. This innovation enhances the feasibility of real-time, non-invasive joint moment prediction for human-robot interaction systems. Through these contributions, Shi is shaping the future of intelligent prosthetics and assistive robotics, offering scalable solutions that integrate machine learning with physiological modeling to improve mobility and rehabilitation outcomes.
Research Focus
Key Achievements
Top Papers
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