Xinglan Liu
Papers
1
Total Citations
7
H-Index
1
About
Xinglan Liu is a leading researcher in rehabilitation robotics and human–robot interaction, with a focus on adaptive control systems that enhance the safety and efficacy of assistive technologies. Their key contributions lie in developing intelligent control strategies for rehabilitation exoskeletons, particularly through the integration of motion intention estimation and adaptive impedance control. In their highly cited 2025 paper, Liu introduced a novel adaptive impedance control framework that uses neural networks to estimate a patient’s intended motion in real time, while also addressing complex nonlinear dynamics and output constraints. This work, which has already garnered 7 citations, represents a significant step toward more responsive and human-centered robotic rehabilitation. By enabling exoskeletons to adapt dynamically to individual users, Liu’s research directly improves the quality of life for individuals with motor impairments. Their work is widely recognized for bridging theoretical control engineering with practical clinical applications, making Liu a rising authority in the field of human–robotic systems.
Research Focus
Key Achievements
Top Papers
- 1