Le Liang

Papers

Total Citations

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About

Le Liang’s research lies at the intersection of human-robot interaction and biomedical signal processing, with a particular focus on rehabilitation exoskeletons. His most cited work introduces a novel surface electromyography (sEMG)-angle model based on Hidden Markov Models (HMM), designed to create more intuitive and responsive human-robot interfaces. By enabling exoskeleton robots to interpret muscle activity and predict joint angles in real time, Liang’s approach addresses a critical challenge in assistive robotics: achieving seamless, natural control that adapts to individual users. This foundational contribution, cited in subsequent studies on rehabilitation robotics and HRI, demonstrates his ability to bridge computational modeling with practical clinical needs. Liang’s work is especially relevant for researchers developing adaptive exoskeletons for stroke rehabilitation or mobility assistance, as it provides a framework for integrating physiological signals into robotic control loops. His focus on user-centered design and real-time adaptability marks him as a promising voice in the growing field of intelligent assistive technologies.