Accelerometer-based Fall Detection

Accelerometer-Based Fall Detection is a fall detection method that utilizes data from accelerometers to identify sudden changes in body motion characteristic of falls, distinguishing it from other fall detection approaches by its reliance on acceleration measurements as the primary sensor modality.

373

Publications

40.9K

Citations

1.2K

Authors

458

Institutions

Publications per year

2017–2026

112

Authors

1.2K

  1. AB
    Alan Bourke

    University of Limerick, Ireland

    13 publications · 644 citations

    11

    h-index

  2. NH
    Nigel H. Lovell

    UNSW Sydney, Australia

    10 publications · 480 citations

    10

    h-index

  3. MR
    Michael R. Narayanan

    UNSW Sydney, Australia

    9 publications · 288 citations

    9

    h-index

  4. SJ
    Stephen J. Redmond

    UNSW Sydney, Australia

    8 publications · 229 citations

    8

    h-index

  5. MG
    Matjaž Gams

    Jožef Stefan Institute, Slovenia

    8 publications · 488 citations

    8

    h-index

1–5 of 1.2K

Venues

  1. Sensors

    25 publications · 2.4K citations

    20

    h-index

  2. IEEE Sensors Journal

    14 publications · 1.6K citations

    14

    h-index

  3. Procedia Computer Science

    5 publications · 298 citations

    5

    h-index

  4. Conference proceedings

    Conference · 4 publications · 375 citations

    4

    h-index

  5. Gait & Posture

    4 publications · 780 citations

    4

    h-index

1–5