Brain-computer Interface Signal Modeling

Brain-Computer Interface Signal Modeling is a computational framework that characterizes the transformation of neural electrophysiological activity into interpretable control signals for external devices, distinguished by its focus on mathematical representation and algorithmic decoding of brain-originated bioelectric patterns within real-time, closed-loop systems.

181

Publications

10.2K

Citations

607

Authors

272

Institutions

Publications per year

2017–2026

70

Authors

607

  1. XG
    Xiaorong Gao

    Tsinghua University, China

    9 publications · 615 citations

    9

    h-index

  2. SG
    Shangkai Gao

    Tsinghua University, China

    6 publications · 509 citations

    6

    h-index

  3. JJ
    Jing Jin

    East China University of Science and Technology, China

    6 publications · 711 citations

    6

    h-index

  4. CG
    Cuntai Guan

    Institute for Infocomm Research, Singapore

    5 publications · 375 citations

    5

    h-index

  5. YW
    Yijun Wang

    Chinese Academy of Sciences, China

    5 publications · 462 citations

    5

    h-index

1–5 of 607

Venues

  1. Journal of Neural Engineering

    11 publications · 636 citations

    11

    h-index

  2. Journal of Neuroscience Methods

    11 publications · 828 citations

    10

    h-index

  3. 8

    h-index

  4. Neural Networks

    8 publications · 1K citations

    8

    h-index

  5. Biomedical Signal Processing and Control

    9 publications · 329 citations

    7

    h-index

1–5