Sheng-Yen Lin

Papers

Total Citations

128

H-Index

About

Sheng-Yen Lin is a leading researcher in rehabilitation robotics, with a primary focus on developing intelligent assistive systems for upper limb and hand recovery after stroke. His most impactful work, cited over 110 times, introduces an innovative assistive control system for an upper limb rehabilitation robot. This system uniquely integrates force/torque sensors with a dynamic human model to simulate natural patient-robot interaction across three critical rehabilitation modes—active, assistive, and passive—allowing for adaptive therapy tailored to individual recovery stages. Lin’s foundational 2012 paper further established the importance of robotic assistive approaches in delivering quantifiable, high-dosage exercise to improve patient outcomes. He has also contributed to the field of hand rehabilitation with a novel joint localizer for precise finger length measurements, a necessary calibration step for hand exoskeleton devices. Through his work, Lin has demonstrated how sensor-integrated kinematic structures can transform rehabilitation from subjective assessment into data-driven, personalized therapy, making significant strides in restoring motor function and quality of life for stroke survivors.