Xianwei Huang
Papers
6
Total Citations
160
H-Index
5
About
Xianwei Huang is a biomedical engineer and rehabilitation robotics researcher whose work sits at the intersection of adaptive control systems, virtual reality, and post-stroke motor recovery. His research has made meaningful contributions to the development of intelligent robotic systems designed to restore fine hand and upper extremity motor function in stroke survivors, a population for whom dexterity deficits profoundly impact daily life. Huang's most influential work explores how combining adaptive, assist-as-needed control algorithms with immersive virtual reality environments can enhance the effectiveness of robot-assisted rehabilitation. His 2017 case study examining these combined effects in chronic stroke patients has garnered 56 citations, while companion clinical studies in subacute populations further validated the approach with real-world patients. Underpinning these clinical investigations is a strong foundation in machine learning-based control, particularly his development of a Reinforcement Learning Neural Network (RLNN) framework for adaptive robot control, cited 22 times, and its subsequent extension using Temporal Difference critic-actor architectures. His 2016 survey of upper extremity rehabilitation robotics, cited 27 times, demonstrates his breadth of knowledge across the field and has served as a useful reference point for emerging researchers. Collectively, Huang's work advances the goal of delivering personalized, neuroplasticity-driven stroke rehabilitation through intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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