Fall Prediction

Fall Prediction is a computational method that distinguishes itself from other activity recognition techniques by forecasting the likelihood of a human fall before its occurrence through analysis of physiological, behavioral, or environmental indicators.

336

Publications

16.3K

Citations

1.6K

Authors

708

Institutions

Publications per year

2017–2026

183

Authors

1.6K

  1. SR
    Stephen R. Lord

    Neuroscience Research Australia, Australia

    7 publications · 754 citations

    7

    h-index

  2. LE
    Leland E. Dibble

    University of Utah, United States

    5 publications · 357 citations

    5

    h-index

  3. KS
    Kimberley S. van Schooten

    Vrije Universiteit Amsterdam, Netherlands

    5 publications · 327 citations

    5

    h-index

  4. JH
    Jaap H. van Dieën

    Vrije Universiteit Amsterdam, Netherlands

    5 publications · 320 citations

    5

    h-index

  5. JT
    James T. Cavanaugh

    University of New England, United States

    4 publications · 301 citations

    4

    h-index

1–5 of 1.6K

Venues

  1. Sensors

    19 publications · 987 citations

    18

    h-index

  2. Scientific Reports

    8 publications · 567 citations

    8

    h-index

  3. IEEE Sensors Journal

    8 publications · 626 citations

    8

    h-index

  4. Clinical Rehabilitation

    6 publications · 245 citations

    6

    h-index

  5. 5

    h-index

1–5