Linfeng Cao
Papers
2
Total Citations
115
H-Index
2
About
Linfeng Cao is a leading researcher in non-invasive brain–computer interfaces (BCIs) and assistive robotics, specializing in shared control strategies that bridge the gap between neural decoding and real-world motor tasks. His work addresses a critical challenge in the field: the poor signal quality of EEG-based BCIs, which often limits the precision and reliability of brain-actuated devices. Cao’s major contributions include the development of a brain-actuated robotic arm system that integrates hybrid BCI with shared control, allowing users to perform reach-and-grasp tasks with greater accuracy and reduced cognitive load. His 2021 paper on this system has garnered 61 citations, while his 2020 study on shared control for multi-object grasping has received 54 citations, reflecting the high impact of his research on the BCI and rehabilitation robotics communities. By combining robot vision with non-invasive neural interfaces, Cao has advanced practical solutions for patients with motor impairments, enabling more intuitive and effective control of assistive devices. His work is notable for its translational focus, directly addressing the usability and performance bottlenecks that have hindered the adoption of brain-controlled robotic arms in daily living activities.
Research Focus
Key Achievements
Top Papers
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- 2