Yu Gong-jing

Beijing University of Posts and Telecommunications

Papers

Total Citations

H-Index

About

Yu Gong-jing is a pioneering researcher at the intersection of neural engineering and assistive robotics, with a primary focus on developing intuitive, hybrid brain-computer interface (BCI) systems. Her most notable contribution is the design of a robotic arm control system that fuses electroencephalogram (EEG) and electromyogram (EMG) signals, addressing critical limitations in conventional BCIs—namely, single-signal reliance, low feature recognition accuracy, and limited output commands. By integrating brain and muscle signals, her work enables more robust, multi-degree-of-freedom control for individuals with motor impairments, offering a pathway toward seamless human-machine collaboration. Though her landmark 2021 paper has garnered 2 citations, its conceptual novelty in mixed-signal processing marks a significant step forward in assistive technology. Gong-jing’s research holds promise for advancing rehabilitation robotics and neuroprosthetics, positioning her as an emerging voice in the quest to bridge neural activity with real-world robotic action. Her work inspires students and researchers to explore how multimodal biological signals can unlock more natural, responsive control systems for those in need.