Papers
1
Total Citations
4
H-Index
1
About
Tan Wei is a pioneering researcher in the field of brain–computer interfaces (BCIs), with a particular focus on noninvasive neural decoding and motor imagery. His most-cited work, "A novel noninvasive brain–computer interface by imagining isometric force levels" (2022), introduces an innovative approach to translating imagined force variations into control signals, expanding the possibilities for BCI applications in rehabilitation and assistive technology. Though early in his career, Tan's contributions are marked by a commitment to bridging cognitive neuroscience and practical engineering, offering new pathways for patients with motor impairments. His research emphasizes the extraction of nuanced neural patterns from electroencephalography (EEG) data, demonstrating that imagined force levels can be reliably classified—a key step toward more intuitive and adaptive BCI systems. With 4 citations to date, this work has already sparked interest in the BCI community for its potential to enhance prosthetic control and neurofeedback training. Tan's dedication to advancing noninvasive interfaces positions him as an emerging voice in neural engineering, where his future work promises to further refine the synergy between human intent and machine response.
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Top Papers
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