Papers

1

Total Citations

15

H-Index

1

About

Cunbo Li is a rising researcher at the forefront of rehabilitation robotics and neural signal processing. His work centers on decoding the intricate interplay between muscle activity and robotic systems, with a particular focus on electromyography (EMG) signal analysis and wearable assistive technologies. In his most-cited 2023 paper, Li introduced a novel wearable master–slave rehabilitation robot that integrates an epidermal array electrode sleeve with a multichannel EMG network. This innovation enables high-resolution measurement of muscle unit interactions, offering a powerful tool for both robotic rehabilitation and the study of movement neural mechanisms. By advancing network analysis of EMG signals, Li’s research provides critical insights into how information propagates across muscle groups, paving the way for more intuitive and effective human–robot interfaces. Though early in his career, his work has already garnered attention, with his leading publication accumulating 15 citations—a strong indicator of its growing impact. Li’s contributions are poised to shape the future of neurorehabilitation, bridging the gap between neural control and robotic assistance.

Research Focus

Key Achievements

1
H-Index
1
Papers
15
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
A Wearable Master–Slave Rehabilitation Robot Based on an Epidermal Array Electrode Sleeve and Multichannel Electromyography Network
15 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: University of Electronic Science and Technology of China

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago