Yonghui Wang
Papers
4
Total Citations
43
H-Index
3
About
Yonghui Wang is a leading researcher at the intersection of rehabilitation robotics and intelligent manipulation systems. His work primarily focuses on two critical domains: robot-assisted neurorehabilitation for stroke patients and autonomous robotic grasping. In his highly cited 2022 study (20 citations), Wang pioneered the use of functional near-infrared spectroscopy (fNIRS) to map brain functional responses during robot-assisted upper-limb therapy in hemiplegic stroke patients, providing the first neurophysiological evidence supporting personalized rehabilitation protocols. This work bridges the gap between clinical therapy and neural recovery mechanisms. In robotic manipulation, Wang developed innovative methods for compliant nursing robot interactions based on human limb biomechanics (2020, 11 citations) and created algorithms to autonomously estimate unknown objects’ center of mass and friction coefficients (2018, 9 citations)—essential parameters for stable grasping. His quantitative motion detection framework for in-hand objects (2019) addresses critical grasp stability issues. With cumulative citations exceeding 40 across his most impactful works, Wang’s research has direct applications in assistive robotics, rehabilitation engineering, and autonomous manipulation, making him a key figure in advancing human-robot interaction technologies for healthcare and industrial applications.
Research Focus
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Top Papers
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