Real-time Eeg Processing

Real-Time EEG Processing is a methodological framework within electroencephalogram analysis that enables the immediate acquisition, preprocessing, feature extraction, and interpretation of EEG signals with minimal latency, distinguishing it from offline or batch-processing approaches by its requirement for continuous, time-constrained neural data transformation and decision-making.

242

Publications

15.3K

Citations

897

Authors

378

Institutions

Publications per year

2017–2026

91

Authors

897

  1. TJ
    Tzyy‐Ping Jung

    University of California San Diego, United States

    12 publications · 2.1K citations

    11

    h-index

  2. OS
    Olga Sourina

    Nanyang Technological University, Singapore

    8 publications · 761 citations

    8

    h-index

  3. SM
    Scott Makeig

    University of California San Diego, United States

    6 publications · 2K citations

    6

    h-index

  4. GC
    Gert Cauwenberghs

    University of California San Diego, United States

    6 publications · 1.4K citations

    6

    h-index

  5. TM
    Tim Mullen

    University of California San Diego, United States

    5 publications · 2K citations

    5

    h-index

1–5 of 897

Venues

  1. Journal of Neural Engineering

    10 publications · 692 citations

    10

    h-index

  2. IEEE Transactions on Biomedical Engineering

    11 publications · 1.4K citations

    10

    h-index

  3. 6

    h-index

  4. Sensors

    5 publications · 240 citations

    5

    h-index

  5. Frontiers in Neuroscience

    5 publications · 823 citations

    5

    h-index

1–5