Yuanliang Meng

Papers

Total Citations

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About

Yuanliang Meng is a researcher at the intersection of artificial intelligence and neurorehabilitation, focusing on developing intelligent systems that empower patients to perform effective motor recovery exercises at home. His major contributions center on creating learning-based agents and frameworks that adapt to individual patient needs, enabling autonomous, structured rehabilitation outside clinical settings. Meng’s most cited work, “A learning-based agent for home neurorehabilitation” (2017, 11 citations), presents an iterative AI system designed to guide and promote proper exercise practice, addressing a critical gap in home-based therapy adherence. His earlier foundational paper, “A learning from demonstration framework to promote home-based neuromotor rehabilitation” (2016, 4 citations), innovatively applies the robot learning paradigm of Learning from Demonstration (LfD) to assist children with motor disabilities, translating embodied robot training techniques into accessible home and community rehabilitation tools. By bridging AI, robotics, and clinical therapy, Meng’s work has laid important groundwork for scalable, personalized neurorehabilitation technologies, offering new pathways for patients to regain motor function independently. His research continues to influence the development of adaptive, patient-centered rehabilitation systems.