Mo Han
Papers
1
Total Citations
4
H-Index
1
About
Mo Han is an emerging researcher at the intersection of human-machine interfaces, prosthetics, and multimodal sensing. His work focuses on developing intelligent control systems for robotic prosthetic hands, with a particular emphasis on improving the quality of life for transradial amputees. His most notable contribution, "Multimodal Fusion of EMG and Vision for Human Grasp Intent Inference in Prosthetic Hand Control" (2021), addresses one of the most persistent challenges in prosthetics research — the unreliability of electromyography-based control systems under real-world conditions such as motion artifacts and muscle fatigue. By integrating EMG signals with computer vision, Han proposes a robust multimodal fusion framework that significantly enhances grasp intent recognition, pushing prosthetic control closer to intuitive, seamless use. Though early in his citation trajectory with 4 citations, his research tackles a high-impact clinical and engineering problem that sits at the convergence of biomedical engineering, robotics, and machine learning. Students and researchers interested in assistive technology, human-robot interaction, or neural signal processing will find Han's interdisciplinary approach a compelling model for translational research with direct humanitarian applications.
Research Focus
Key Achievements
Top Papers
- 1