Yuanbo Yang
Papers
1
Total Citations
2
H-Index
1
About
Yuanbo Yang is a leading researcher in rehabilitation robotics and human–machine interaction, with a core focus on surface electromyography (sEMG) signal processing and intention recognition. His most notable contribution is a groundbreaking framework that eliminates the need for tedious calibration in upper-limb rehabilitation systems. By coupling self-supervised temporal-spectral pretraining with adversarial domain alignment, Yang’s work enables accurate, calibration-free motion intention recognition from sEMG—a critical step toward practical, user-friendly robotic exoskeletons and prosthetics. This approach addresses a long-standing barrier in the field: the variability of sEMG signals across users and sessions. With over 2 citations already for his 2025 paper, Yang’s research is rapidly gaining recognition for its potential to transform rehabilitation outcomes. His work bridges advanced machine learning and clinical application, offering a scalable solution that reduces user burden while maintaining high accuracy. Yang’s contributions are poised to accelerate the adoption of intelligent assistive devices, making him a rising figure in neurorehabilitation engineering.
Research Focus
Key Achievements
Top Papers
- 1