Papers
13
Total Citations
192
H-Index
8
About
Hosu Lee is a robotics and rehabilitation engineering researcher whose work sits at the intersection of mechanical design, control systems, and clinical applications for motor recovery. Lee's research spans cable-driven parallel robots, lower-limb gait rehabilitation devices, trunk stabilization systems, and haptic assistive technologies — areas in which he has made meaningful contributions to both engineering design and therapeutic efficacy. His most influential work, a 2016 study on the kinematic optimization of planar cable-driven parallel robots (65 citations), established foundational principles for wrench-closure trajectory planning in rehabilitation contexts. Building on this, Lee developed a series of innovative systems including a single-DOF Jansen mechanism-based gait device, a haptic robotic companion for overground walking, and a trunk rehabilitation robot capable of modulating seat and leg support conditions to isolate and strengthen core musculature. More recently, Lee has explored machine learning for adaptive difficulty calibration in balance training and multi-modal biofeedback using transcutaneous electrical nerve stimulation, reflecting a growing emphasis on personalized, data-driven rehabilitation. His comparative clinical studies on haptic canes for stroke survivors further demonstrate a commitment to translating engineering innovations into real-world patient outcomes. With over 180 cumulative citations, Lee's body of work represents a rigorous and human-centered approach to rehabilitation robotics.
Research Focus
Key Achievements
Top Papers
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- 6Control of cable-driven parallel robot for gait rehabilitation15 citations · 2015
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