Shupei Li
Papers
1
Total Citations
4
H-Index
1
About
Shupei Li is a leading researcher in the field of rehabilitation robotics and human–machine interaction, with a primary focus on intelligent control systems for lower limb exoskeletons. Their most influential work, "A Novel F-SVM based on PSO for Gait Phase Recognition in Lower Limb Exoskeleton" (2023), addresses a critical challenge in assistive robotics: achieving accurate, real-time gait phase detection under varying walking speeds while maintaining lightweight hardware. By integrating particle swarm optimization (PSO) with a radius-margin-based support vector machine (SVM), Li’s model significantly enhances classification precision for kinematic and dynamic gait data. This contribution has garnered 4 citations and is foundational for developing more responsive, adaptive exoskeletons that improve mobility for individuals with lower-limb impairments. Li’s research bridges the gap between theoretical machine learning and practical robotic control, demonstrating a clear impact on the design of efficient, user-centric assistive devices. Their work is essential reading for students and engineers aiming to advance human–robot synergy in rehabilitation technologies.
Research Focus
Key Achievements
Top Papers
- 1