Papers
1
Total Citations
6
H-Index
1
About
Anmin Gong is a leading researcher in brain-computer interfaces (BCIs) and neural signal processing, with a focus on advancing non-invasive neurotechnology for real-world applications. His work centers on decoding electroencephalography (EEG) signals to enable intuitive human-machine interaction, particularly through novel motor imagery paradigms. Gong’s most cited paper, “A novel strategy for driving car brain–computer interfaces: Discrimination of EEG-based visual-motor imagery” (2021, 6 citations), introduces a groundbreaking approach to BCI-controlled driving by distinguishing visual-motor imagery (VMI) from traditional kinesthetic motor imagery. This work addresses a critical gap in BCI research, proposing innovative feature extraction methods that enhance the reliability and practicality of VMI-based systems for clinical and assistive technologies. By pioneering VMI paradigms, Gong expands the possibilities for BCIs in rehabilitation, smart environments, and autonomous vehicle control. His contributions are shaping the future of neural interfaces, offering scalable solutions for patients with motor impairments and advancing the field toward seamless brain-driven interaction.
Research Focus
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Top Papers
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