Fall Recognition

Fall Recognition is a computational method within human activity analysis that specifically identifies and classifies instances of human falls from sensor or video data through distinctive pattern-based detection mechanisms.

1.3K

Publications

71.3K

Citations

3.8K

Authors

1.2K

Institutions

Publications per year

2017–2026

614

Authors

3.8K

  1. MS
    Marjorie Skubic

    University of Missouri, United States

    17 publications · 1.8K citations

    15

    h-index

  2. MP
    Mihail Popescu

    University of Missouri, United States

    14 publications · 1K citations

    14

    h-index

  3. MR
    Marilyn Rantz

    University of Missouri, United States

    12 publications · 1K citations

    12

    h-index

  4. NH
    Nigel H. Lovell

    UNSW Sydney, Australia

    13 publications · 2K citations

    11

    h-index

  5. MG
    Matjaž Gams

    Jožef Stefan Institute, Slovenia

    10 publications · 542 citations

    10

    h-index

1–5 of 3.8K

Venues

  1. Sensors

    76 publications · 4.6K citations

    36

    h-index

  2. IEEE Sensors Journal

    34 publications · 2.8K citations

    26

    h-index

  3. IEEE Access

    37 publications · 1.7K citations

    24

    h-index

  4. IEEE Journal of Biomedical and Health Informatics

    17 publications · 2.3K citations

    17

    h-index

  5. Expert Systems with Applications

    16 publications · 918 citations

    16

    h-index

1–5