Papers
17
Total Citations
263
H-Index
10
About
Baoguo Xu is a prominent researcher at the intersection of brain-computer interfaces (BCIs), neural engineering, and rehabilitation robotics. His work focuses on harnessing electroencephalogram (EEG) signals to restore and augment motor function in individuals with neurological conditions, particularly stroke survivors and those with upper-limb paralysis. Xu's most significant contributions lie in developing robot-assisted rehabilitation systems driven by motor imagery EEG, pioneering work that dates to 2011 and has garnered nearly 40 citations. He has advanced the field by designing hybrid brain-machine interfaces that combine gaze-tracking with neural signals, enabling semi-autonomous robotic arm control for individuals with severely limited movement. His more recent studies on decoding reach-and-grasp movements and hand kinematics from noninvasive EEG represent meaningful strides toward intuitive neuroprosthesis control, collectively accumulating over 50 citations. Beyond neural decoding, Xu has made notable contributions to safety-supervisory frameworks for rehabilitation robots using impedance and fuzzy logic control, and has developed continuous shared-control strategies for both robotic arms and mobile robots. Altogether, his body of work—exceeding 220 citations—reflects a sustained commitment to translating neuroscience into practical assistive technologies that meaningfully improve patient quality of life.
Research Focus
Key Achievements
Top Papers
- 1Robot-Aided Upper-Limb Rehabilitation Based on Motor Imagery EEG39 citations · 2011
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- 8Robotic neurorehabilitation system design for stroke patients14 citations · 2015
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