Lei Yu-chen
Papers
1
Total Citations
8
H-Index
1
About
Lei Yu-chen is a leading researcher in biomechatronics and human–machine interaction, with a focus on improving the control of wearable robotic systems through advanced signal processing and machine learning. Their most cited work, “Influence of Input Features and EMG Type on Ankle Joint Torque Prediction With Support Vector Regression” (2023, 8 citations), investigates how different electromyographic (EMG) input features affect the accuracy of ankle joint torque prediction under both isometric and dynamic conditions. By systematically evaluating support vector regression models, Lei’s research provides critical insights for developing more reliable, real-time control strategies for exoskeletons and prosthetic devices. This work addresses a fundamental challenge in assistive robotics: ensuring that predicted joint torques remain robust across varying movement contexts. Lei’s contributions are instrumental in bridging the gap between raw biological signals and practical, high-performance robotic control, offering a pathway toward more intuitive and responsive wearable technologies. Their findings are directly applicable to rehabilitation engineering and human augmentation, making Lei Yu-chen a key figure in advancing EMG-driven control systems.
Research Focus
Key Achievements
Top Papers
- 1