Brain-computer Interface Signal Processing

Brain–Computer Interface Signal Processing is a specialized methodology within neurophysiological signal analysis that transforms electrophysiological brain activity, particularly electroencephalogram signals, into machine-readable commands through feature extraction, classification, and real-time decoding mechanisms to establish direct communication pathways between the brain and external devices.

2.2K

Publications

148.7K

Citations

5.3K

Authors

1.6K

Institutions

Publications per year

2017–2026

802

Authors

5.3K

  1. AK
    Andrea Kübler

    University of Würzburg, Germany

    47 publications · 7.6K citations

    42

    h-index

  2. JR
    Jonathan R. Wolpaw

    New York State Department of Health, United States

    40 publications · 15.8K citations

    36

    h-index

  3. BB
    Benjamin Blankertz

    Technische Universität Berlin, Germany

    41 publications · 10.2K citations

    33

    h-index

  4. GM
    Gernot Müller-Putz

    Graz University of Technology, Austria

    40 publications · 3.8K citations

    30

    h-index

  5. DJ
    Dennis J. McFarland

    New York State Department of Health, United States

    31 publications · 11.3K citations

    30

    h-index

1–5 of 5.3K

Venues

  1. 66

    h-index

  2. Journal of Neural Engineering

    126 publications · 11.6K citations

    53

    h-index

  3. IEEE Transactions on Biomedical Engineering

    63 publications · 14.5K citations

    46

    h-index

  4. PLoS ONE

    41 publications · 3.7K citations

    34

    h-index

  5. Journal of Neuroscience Methods

    47 publications · 4.6K citations

    28

    h-index

1–5