Papers
14
Total Citations
264
H-Index
8
About
Sung Yul Shin is a leading researcher at the intersection of humanoid robotics and rehabilitation engineering, whose work bridges the gap between human-like manipulation and assistive gait technologies. His early contributions focused on enabling humanoid robots to perform natural, human-like dual-arm object manipulation in complex environments, developing virtual dynamics models and grasp synthesis algorithms that allow robots to handle unknown objects with dexterity. These foundational studies, including his 2014 paper on human-like motion generation for manipulation (76 citations), established methods for real-time motion transition and control that remain influential in the field. More recently, Shin has made transformative contributions to soft robotic exosuits and gait rehabilitation. His pilot study on soft exosuit-augmented high-intensity gait training for stroke survivors (50 citations) demonstrated significant improvements in walking ability, showcasing the clinical potential of lightweight, portable assistive devices. He has also designed innovative single degree-of-freedom robotic gait trainers that reduce therapy costs while providing effective, natural gait patterns, with kinematic comparisons (22 citations) validating their efficacy. His work on inertial motion capture sensitivity (17 citations) has advanced wearable sensor technology for tracking recovery, making rehabilitation more accessible and data-driven. Through these achievements, Shin is shaping the future of both humanoid robotics and neurorehabilitation.
Research Focus
Key Achievements
Top Papers
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- 5Kinematic comparison of single degree-of-freedom robotic gait trainers22 citations · 2021
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- 7Humanoid's dual arm object manipulation based on virtual dynamics model11 citations · 2012
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- 10Design of an 1 DOF Assistive Knee Joint for a Gait Rehabilitation Robot5 citations · 2013