Yixing Liu
Papers
3
Total Citations
48
H-Index
2
About
Yixing Liu is a leading researcher in the field of wearable robotics and human–machine interaction, with a primary focus on neural control of robotic exoskeletons and rehabilitation engineering. Their major contributions center on developing muscle synergy-inspired methods that decode human movement intentions from wearable sensor data, enabling seamless transitions between locomotion modes and accurate joint moment prediction using minimal electromyography sensors. Notably, Liu’s 2021 study on detecting human movement intentions via sensor fusion has garnered 38 citations, while their work on muscle synergies for joint moment prediction has been cited 8 times. More recently, Liu has advanced human-in-the-loop optimization techniques, as demonstrated in their 2025 paper on optimizing exoskeleton assistance for dropfoot gait (2 citations), which holds promise for personalized rehabilitation. By bridging biomechanics, signal processing, and control theory, Liu’s research directly addresses the challenge of making exoskeletons intuitive and effective for users with motor disorders. Their work stands out for its practical focus on reducing sensor complexity while maintaining high accuracy, a key step toward translating robotic assistance from labs to daily life.
Research Focus
Key Achievements
Top Papers
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