Papers
40
Total Citations
557
H-Index
14
About
Won-Kyung Song is a leading figure in rehabilitation robotics, whose work has profoundly shaped assistive technologies for individuals with disabilities and the elderly. His research centers on developing intelligent robotic systems—from wheelchair-mounted arms to self-feeding devices—that restore independence in activities of daily living. Song’s seminal contributions include the KARES (KAIST Rehabilitation Engineering System) project, a pioneering wheelchair-based robotic arm integrating vision and force sensors for intuitive human-robot interaction. His 1999 paper on KARES has garnered 55 citations, while his 2014 kinematic analysis of upper extremity movement in hemiplegic subjects—his most cited work with 85 citations—provides foundational insights for stroke rehabilitation. Song has also advanced clinical applications through randomized controlled trials on robot-assisted reach training for chronic stroke survivors, demonstrating significant improvements in upper limb function. Notably, his usability studies on the KNRC self-feeding robot address the critical gap between lab prototypes and real-world practicality. As a key researcher at Korea’s National Rehabilitation Center, Song’s translational work bridges engineering and clinical practice, offering a roadmap for deploying assistive robots that enhance quality of life.
Research Focus
Key Achievements
Top Papers
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- 3Novel Assistive Robot for Self-Feeding40 citations · 2012
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- 7Usability test of KNRC self-feeding robot23 citations · 2013
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