Yanxin Wang
Papers
4
Total Citations
134
H-Index
4
About
Yanxin Wang is a pioneering researcher at the intersection of brain-machine interfaces (BMIs), human-robot interaction, and assistive robotics, with a focused mission to restore independence for individuals living with paralysis and motor impairments. Wang's most celebrated contribution is the development of hybrid gaze-brain machine interface systems that seamlessly integrate electroencephalogram (EEG) signals with gaze-tracking technology to enable intuitive control of robotic arms — work that has garnered over 70 citations since its 2017 publication. A defining theme across Wang's research is the challenge of translating neural signals into precise, reliable robotic actions; to address this, Wang pioneered the incorporation of augmented reality feedback into closed-loop BMI systems, dramatically improving user accuracy and efficiency during complex tasks such as object grasping and lifting. Wang further advanced the field through continuous shared control frameworks and semi-autonomous reaching strategies, reducing cognitive burden on users while preserving meaningful agency. Collectively accumulating over 130 citations, Wang's body of work represents a significant stride toward practical, real-world assistive technologies that could meaningfully transform the daily lives of people with severe physical disabilities.
Research Focus
Key Achievements
Top Papers
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