Papers
8
Total Citations
74
H-Index
5
About
Musong Lin is a leading researcher in rehabilitation robotics, specializing in lower limb robotic systems for stroke recovery and mobility-impaired patients. His work centers on developing intelligent, multi-sensor rehabilitation robots that enhance patient participation and training outcomes. Lin's major contributions include the design of a 4-DOF workspace lower limb rehabilitation robot capable of hip adduction/abduction training—a feature often missing in existing devices—and the integration of adaptive admittance control schemes with virtual reality interaction for strength training. His research has been cited over 70 times, with his most influential paper, "Detection of Participation and Training Task Difficulty Applied to the Multi-Sensor Systems of Rehabilitation Robots" (2019), garnering 21 citations for its cost-effective approach to measuring patient engagement. Lin has also pioneered human-robot cooperative strength training with robust admittance control, addressing knee soft tissue protection in elderly stroke survivors. Notable achievements include the development of the LLR-II robot with direct teaching control, enabling physiotherapists to plan personalized trajectories, and a virtual reality training system that gamifies bike riding to motivate patients. His work bridges mechanical design, adaptive control, and interactive therapy, advancing accessible, patient-centered rehabilitation technology.
Research Focus
Key Achievements
Top Papers
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- 5Virtual reality training system based on lower limb rehabilitation robot7 citations · 2018
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