Challenges and Future Development of Neural Signal Decoding and Brain-Computer Interface Technology
DOI:
https://doi.org/10.71222/gsxrer80Keywords:
brain-computer interface, neural signal decoding, deep learning, system structureAbstract
Brain-computer interface technology can decode neural signals and realize two-way information exchange between brain and computer. The development of brain-computer interface technology is gradually becoming the mainstream direction of neuro-engineering and intelligent control research. In this paper, the structural characteristics and decoding methods of BCI system are described in detail, and the key challenges of neural signal stability and individual model design, real-time performance and security are discussed, as well as the technological development of low invasive acquisition, multi-modal fusion, adaptive algorithms and brain-computer interactive intelligence, comprehensive simulation and comparative analysis. It is expected to provide theoretical reference for the practical application and intelligent research of BCI system.
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