Papers
69
Total Citations
458
H-Index
11
About
Shuoyu Wang is a prominent robotics and rehabilitation engineering researcher whose work sits at the intersection of human-robot interaction, assistive technologies, and intelligent control systems. His research focuses primarily on rehabilitation robotics, adaptive control, wearable sensing, and autonomous service robots, with particular emphasis on improving quality of life for individuals with mobility impairments. Wang's most impactful contributions include the development of adaptive sliding-mode control frameworks for human support robots using disturbance observers, which has garnered 36 citations, and innovative gait recognition approaches for walking assist robots employing extended set membership filtering (29 citations). His work on intelligent rehabilitation robots capable of seamlessly switching between passive and active training modes (25 citations) addresses a critical gap in clinical rehabilitation practice caused by physiotherapist shortages. Beyond rehabilitation, Wang has contributed meaningfully to path planning algorithms for home service robot arms, wearable multisensor systems for human motion analysis, and automated Parkinsonian gait assessment — each accumulating 20–25 citations. His interdisciplinary breadth also extends to desire-driven reasoning for personal care robots and autonomous navigation in construction environments. Collectively, Wang's portfolio reflects a sustained commitment to advancing intelligent, human-centered robotic systems that meaningfully support vulnerable populations and enhance healthcare delivery.
Research Focus
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Top Papers
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- 10Desire-Driven Reasoning for Personal Care Robots14 citations · 2019