Fall Detection Devices

Fall Detection Devices is an assistive technology that automatically identifies unintentional falls through sensor-based monitoring and distinguishes them from other movements using predefined kinematic thresholds or machine learning algorithms.

235

Publications

30.2K

Citations

909

Authors

324

Institutions

Publications per year

2017–2026

77

Authors

909

  1. SJ
    Stephen J. Redmond

    UNSW Sydney, Australia

    5 publications · 448 citations

    5

    h-index

  2. NH
    Nigel H. Lovell

    UNSW Sydney, Australia

    5 publications · 448 citations

    5

    h-index

  3. NN
    Norbert Noury

    Translational Innovation in Medicine and Complexity, France

    4 publications · 199 citations

    4

    h-index

  4. PM
    P. Malcovati

    University of Pavia, Italy

    3 publications · 93 citations

    3

    h-index

  5. CH
    Chih-Ning Huang

    National Yang Ming Chiao Tung University, Taiwan

    3 publications · 239 citations

    3

    h-index

1–5 of 909

Venues

  1. Sensors

    7 publications · 925 citations

    7

    h-index

  2. Journal of Telemedicine and Telecare

    3 publications · 329 citations

    3

    h-index

  3. IEEE Transactions on Consumer Electronics

    3 publications · 404 citations

    3

    h-index

  4. 3

    h-index

  5. IEEE Sensors Journal

    3 publications · 217 citations

    3

    h-index

1–5