Adaptive Brain-computer Interfaces

Adaptive Brain-Computer Interfaces is a type of brain-computer interface that dynamically adjusts its decoding algorithms or system parameters in real time based on changes in neural signals or user performance to maintain or improve communication accuracy and efficiency.

177

Publications

14.2K

Citations

547

Authors

247

Institutions

Publications per year

2017–2026

42

Variants

Adaptive Bcis

Authors

547

  1. JD
    José del R. Millán

    École Polytechnique Fédérale de Lausanne, Switzerland

    10 publications · 1.7K citations

    10

    h-index

  2. RS
    Reinhold Scherer

    Graz University of Technology, Austria

    11 publications · 737 citations

    10

    h-index

  3. CV
    Carmen Vidaurre

    Technische Universität Berlin, Germany

    8 publications · 820 citations

    8

    h-index

  4. BB
    Benjamin Blankertz

    Technische Universität Berlin, Germany

    7 publications · 2K citations

    7

    h-index

  5. JR
    Jonathan R. Wolpaw

    New York State Department of Health, United States

    6 publications · 2.9K citations

    6

    h-index

1–5 of 547

Venues

  1. 16

    h-index

  2. Journal of Neural Engineering

    18 publications · 1.5K citations

    16

    h-index

  3. IEEE Transactions on Biomedical Engineering

    8 publications · 715 citations

    8

    h-index

  4. PLoS ONE

    5 publications · 231 citations

    5

    h-index

  5. Frontiers in Human Neuroscience

    5 publications · 291 citations

    5

    h-index

1–5