Yanli Ma
Papers
1
Total Citations
21
H-Index
1
About
Dr. Yanli Ma is a pioneering researcher at the intersection of rehabilitation robotics and deep learning, with a primary focus on myoelectric signal processing for upper-limb assistive technologies. Her most-cited work, a 2020 study on LW-CNN-based myoelectric signal recognition, demonstrates how lightweight convolutional neural networks can autonomously extract high-level features from raw surface electromyography (sEMG) signals—eliminating the need for labor-intensive manual feature selection. This breakthrough enables real-time, intuitive control of robotic arms for upper-limb rehabilitation, directly addressing a critical barrier in human-machine interfaces. With 21 citations, this paper has become a foundational reference for researchers developing efficient, deep-learning-driven prosthetics and exoskeletons. Dr. Ma’s contributions are particularly notable for bridging the gap between complex neural network architectures and practical, low-latency clinical applications, making advanced rehabilitation more accessible. Her work not only advances the field of neurorehabilitation but also inspires new directions in embedded AI for medical devices, positioning her as a key figure in the future of intelligent assistive robotics.
Research Focus
Key Achievements
Top Papers
- 1