Lee Ho-Chang

Seoul National University, Korea Advanced Institute of Science and Technology

Papers

Total Citations

295

H-Index

About

Lee Ho-Chang is a leading researcher at the intersection of soft robotics, machine learning, and rehabilitation engineering. His work focuses on developing intelligent, adaptive soft robotic systems that can safely interact with humans and deformable objects—a critical challenge in assistive technology. His most impactful contribution is a comprehensive review of machine learning methods in soft robotics (2021), which has garnered 249 citations and serves as a foundational resource for the field, addressing the complex modeling, calibration, and control issues inherent in soft materials. Ho-Chang has also made significant strides in rehabilitation technology, notably developing a multiple hand posture rehabilitation system that integrates vision-based intention detection with a soft-robotic glove (2024, 29 citations). This system enables stroke survivors to perform active rehabilitation by translating their intended movements into precise finger assistance. Further advancing wearable robotics, he pioneered a method for learning fingertip forces to grasp deformable objects using a tendon-sheath mechanism (2021, 17 citations), solving a key problem in ensuring safe and effective grasping without causing excessive deformation. Through these innovations, Ho-Chang is shaping the future of soft, intelligent robotic systems for human assistance and rehabilitation.