Yongcheng Li

Chinese Academy of Sciences

Papers

1

Total Citations

58

H-Index

1

About

Dr. Yongcheng Li is a leading researcher at the intersection of neural engineering and human-machine interaction, with a primary focus on dexterous robotic control and rehabilitation technologies. His most impactful work centers on decoding human motor intent from surface electromyography (sEMG) signals, where he has pioneered advanced deep learning architectures for continuous finger kinematics estimation. In his highly cited 2022 paper, Dr. Li introduced a novel CNN-Attention network that dramatically improves the precision of simultaneous and proportional control for robotic hands, achieving 58 citations and setting a new benchmark in the field. This contribution addresses a critical challenge in both industrial automation and rehabilitation scenarios, enabling more natural, intuitive prosthetic control. Beyond this flagship work, his research portfolio spans neural signal processing, wearable robotics, and assistive technologies. Dr. Li’s innovations have significant implications for restoring motor function in individuals with limb loss or neurological disorders, bridging the gap between human intent and machine action. His work continues to shape the future of intelligent, human-centered robotic systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
58
Total Citations
58
Avg Citations/Paper
🏆 Most Cited Paper
A CNN-Attention Network for Continuous Estimation of Finger Kinematics from Surface Electromyography
58 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Chinese Academy of Sciences

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago