Papers
13
Total Citations
278
H-Index
8
About
XU Bao-guo is a prominent researcher at the intersection of brain-machine interfaces (BMI), human-robot interaction, and rehabilitation robotics. His work spans two deeply interconnected domains: developing intelligent BCI systems for assistive robotic control and advancing robot-aided rehabilitation for stroke survivors and individuals with physical disabilities. Among his most influential contributions is his pioneering work on hybrid BCI-controlled robotic arms, integrating electroencephalography, eye tracking, computer vision, and augmented reality feedback to enable paralyzed individuals to perform complex grasping tasks with greater precision and independence. His 2017 paper on closed-loop hybrid gaze BMI-based robotic arm control has garnered 72 citations, while his 2022 continuous hybrid BCI control system has accumulated 65 citations, reflecting sustained community recognition of his innovations. Equally significant is his work in rehabilitation robotics, where he has developed adaptive hierarchical control frameworks, safety supervisory strategies, and humanized passive training systems tailored to stroke patients' biomechanical needs. These contributions have helped bridge the gap between clinical rehabilitation requirements and intelligent robotic assistance. With over 270 total citations across his body of work, XU Bao-guo's research continues to meaningfully advance assistive technology and neurorehabilitation engineering.
Research Focus
Key Achievements
Top Papers
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- 4A Novel Human-Robot Cooperative Method for Upper Extremity Rehabilitation31 citations · 2017
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- 8Interested Object Detection based on Gaze using Low-cost Remote Eye Tracker10 citations · 2019
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