Papers
1
Total Citations
4
H-Index
1
About
Xinrun He is a leading researcher in rehabilitation robotics and human-machine interaction, with a focus on lower limb exoskeleton systems for hemiplegic patients. His most cited work, "Hip Joint Trajectory Generation Based on Human Limb Motion Synergy" (2022, 4 citations), introduces a novel approach to trajectory generation that leverages natural human limb coordination patterns. This breakthrough enables more intuitive and adaptive control of exoskeleton robots, significantly enhancing human-machine collaboration during rehabilitation training. By modeling the synergistic relationships between limb segments, He's method allows exoskeletons to generate smoother, more natural hip joint trajectories that mirror healthy gait patterns. His research directly addresses the critical challenge of improving movement recovery outcomes for individuals with motor impairments. Through his innovative trajectory generation techniques, He has laid important groundwork for developing next-generation assistive devices that can better interpret and respond to user intent, ultimately helping patients regain mobility and independence more effectively.
Research Focus
Key Achievements
Top Papers
- 1Hip Joint Trajectory Generation Based on Human Limb Motion Synergy4 citations · 2022