Rule-based Fall Detection

Rule-Based Fall Detection is a fall detection method that uses predefined logical, threshold-based, or heuristic rules derived from domain knowledge to distinguish fall events from non-fall activities in sensor or video data.

10

Publications

493

Citations

33

Authors

21

Institutions

Publications per year

2017–2026

3

Authors

33

  1. GV
    G. Virone

    Translational Innovation in Medicine and Complexity, France

    1 publications · 104 citations

    1

    h-index

  2. AB
    Abderrahmane Boubezoul

    Paris-Est Sup, France

    1 publications · 33 citations

    1

    h-index

  3. MS
    Marina Sokolova

    University of Ottawa, Canada

    1 publications · 43 citations

    1

    h-index

  4. SC
    Simon Coupland

    De Montfort University, United Kingdom

    1 publications · 15 citations

    1

    h-index

  5. MP
    Mihail Popescu

    University of Missouri, United States

    1 publications · 15 citations

    1

    h-index

1–5 of 33

Venues

  1. Sensors

    2 publications · 151 citations

    2

    h-index

  2. Control Engineering Practice

    1 publications · 33 citations

    1

    h-index

  3. Journal of Intelligent & Fuzzy Systems

    1 publications · 43 citations

    1

    h-index

  4. Applied Soft Computing

    1 publications · 52 citations

    1

    h-index

  5. International Journal of Artificial Intelligence Tools

    IJAIT · 1 publications · 16 citations

    1

    h-index

1–5