Zongyan Yao
Papers
1
Total Citations
5
H-Index
1
About
Zongyan Yao is a leading researcher in intelligent prosthetics and human-machine interaction, with a focus on integrating advanced machine learning with biomedical engineering. His most notable contribution is the development of a wireless, sEMG-controlled prosthetic hand that combines a tiny CNN-Transformer model with force feedback, enabling the classification of 21 distinct hand gestures from surface electromyography signals. Remarkably, this model achieves high accuracy with a compact size of just 169 kB, making it suitable for real-time, embedded applications. Yao’s work addresses critical challenges in prosthetic control, including gesture diversity and computational efficiency, while enhancing user experience through tactile feedback. His 2023 paper has already garnered significant attention, reflecting the growing impact of his research on assistive technology. By bridging deep learning and biomechatronics, Yao is paving the way for more intuitive, responsive, and accessible prosthetic devices, with potential applications in rehabilitation and human augmentation.
Research Focus
Key Achievements
Top Papers
- 1