Muzi Xu
Papers
1
Total Citations
56
H-Index
1
About
Muzi Xu is a rising researcher at the intersection of wearable technology, neuroscience, and human-robot interaction. Their work focuses on decoding human motion intention—the neural and physiological signals that precede movement—to create seamless interfaces between humans and assistive devices. Xu’s most-cited paper, “From brain to movement: Wearables-based motion intention prediction across the human nervous system” (2023, 56 citations), provides a comprehensive framework for predicting movement intent using energy-efficient, self-powered wearable sensors. This work bridges the gap between brain signals and physical action, enabling more natural control of rehabilitation and assistive robotics. By integrating nanotechnology-based smart systems, Xu addresses critical challenges in real-time motion prediction, offering transformative potential for individuals with motor impairments. Their research has quickly gained traction, reflecting its importance in advancing human-machine collaboration. Xu’s contributions are paving the way for next-generation wearable systems that are not only intelligent but also autonomous and sustainable, marking a significant step toward intuitive, responsive prosthetics and exoskeletons.
Research Focus
Key Achievements
Top Papers
- 1