Anxiety Detection

Anxiety Detection is a computational method that identifies and classifies indicators of anxiety within multimodal physiological, behavioral, or linguistic data to distinguish it from other affective states in affective computing systems.

129

Publications

5.3K

Citations

539

Authors

264

Institutions

Publications per year

2017–2026

85

Authors

539

  1. AK
    Azadeh Kushki

    University of Toronto, Canada

    4 publications · 163 citations

    4

    h-index

  2. NS
    Nilanjan Sarkar

    Vanderbilt University, United States

    4 publications · 372 citations

    4

    h-index

  3. BA
    Bethany A. Teachman

    University of Virginia, United States

    2 publications · 83 citations

    3

    h-index

  4. LE
    Laura E. Barnes

    University of Virginia, United States

    2 publications · 83 citations

    3

    h-index

  5. WW
    Wanhui Wen

    Southwest University, China

    3 publications · 106 citations

    3

    h-index

1–5 of 539

Venues

  1. IEEE Access

    2 publications · 42 citations

    3

    h-index

  2. 3

    h-index

  3. Biomedical Signal Processing and Control

    2 publications · 358 citations

    3

    h-index

  4. IEEE Transactions on Affective Computing

    TAC · 3 publications · 195 citations

    3

    h-index

  5. IEEE Transactions on Biomedical Engineering

    2 publications · 101 citations

    2

    h-index

1–5