Xiaowei Song
Papers
1
Total Citations
5
H-Index
1
About
Xiaowei Song is a leading researcher in rehabilitation robotics and human–machine interaction, with a primary focus on exoskeleton systems and neuromuscular control. Her most-cited work, “Construction and analysis of muscle functional network for exoskeleton robot” (2019, 5 citations), pioneers a novel approach to decoding surface electromyography (EMG) signals by constructing muscle functional networks. This contribution enables more intuitive, human-centered control of exoskeleton nursing robots, addressing a critical challenge in assistive technology: balancing machine precision with the wearer’s voluntary movement. By identifying spatial and temporal patterns in muscle activation, Song’s research lays the groundwork for smarter, safer co-drive systems that can adapt to individual users. Her work directly impacts the design of next-generation rehabilitation devices, with potential applications in stroke recovery, elderly care, and industrial assistance. Though early in her career, Song’s integration of network science with biomechanics marks her as an emerging voice in the field, bridging the gap between neural signal processing and practical robotic control.
Research Focus
Key Achievements
Top Papers
- 1