Xiaotian Liu
Papers
1
Total Citations
5
H-Index
1
About
Xiaotian Liu’s research centers on human-robot interaction, rehabilitation robotics, and the biomechanical analysis of exoskeleton systems. His most notable contribution lies in the construction and analysis of muscle functional networks for exoskeleton robots, a critical step toward improving human-machine co-drive systems. By examining surface electromyography (EMG) signals during patient-moving tasks, Liu has advanced the identification of spatial and temporal muscle activation patterns, enabling more intuitive and responsive exoskeleton control. His work directly addresses the challenge of integrating human intent with robotic assistance, particularly in nursing and rehabilitation contexts. With over 5 citations for his foundational 2019 paper, Liu’s research is gaining traction among engineers and clinicians seeking to enhance assistive technology. His achievements include developing frameworks that bridge physiological signal analysis and robotic actuation, laying groundwork for smarter, safer exoskeletons. For students and researchers in robotics and biomedical engineering, Liu’s work offers a compelling example of how muscle network analysis can transform human-robot collaboration in healthcare.
Research Focus
Key Achievements
Top Papers
- 1