To-Liang Hsu
Papers
2
Total Citations
5
H-Index
2
About
To-Liang Hsu is a researcher at the intersection of rehabilitation robotics and biosignal processing, with a primary focus on developing intelligent assistive technologies for stroke survivors. His work centers on electromyography (EMG)-based control systems for robotic hand orthoses, addressing the critical challenge of intent inferral in clinical populations. Hsu’s major contribution is the introduction of **ChatEMG**, a novel framework that leverages synthetic data generation to overcome the fundamental barriers of limited and highly variable EMG data collection. By creating realistic, diverse training datasets, his approach enables machine learning classifiers to generalize across different subjects, sessions, and conditions—a persistent hurdle in myoelectric control. This innovation has the potential to make prosthetic and orthotic devices more robust and accessible. Though early in his career, with his flagship paper accumulating 3 citations, the work has already been recognized for its practical significance in rehabilitation engineering. Hsu’s research promises to accelerate the deployment of adaptive, user-friendly robotic aids, directly impacting the quality of life for individuals with motor impairments.
Research Focus
Key Achievements
Top Papers
- 1
- 2