Edge-based Fall Detection

Edge-Based Fall Detection is a fall detection framework that performs real-time data processing and analysis on local edge devices rather than centralized servers, thereby reducing latency, preserving privacy, and enabling immediate response in human activity monitoring systems.

18

Publications

1.3K

Citations

74

Authors

35

Institutions

Publications per year

2017–2026

15

Authors

74

  1. BL
    Bor-Shing Lin

    National Taipei University, Taiwan

    2 publications · 70 citations

    2

    h-index

  2. CP
    Chih‐Wei Peng

    Taipei Medical University, Taiwan

    2 publications · 70 citations

    2

    h-index

  3. HH
    Hung‐Kai Hsu

    National Tsing Hua University, Taiwan

    2 publications · 70 citations

    2

    h-index

  4. IL
    I‐Jung Lee

    National Research Institute of Chinese Medicine, Taiwan

    2 publications · 70 citations

    2

    h-index

  5. IL
    Ignacio Lacalle

    Universitat Politècnica de València, Spain

    1 publications · 14 citations

    1

    h-index

1–5 of 74

Venues

  1. IEEE Access

    3 publications · 126 citations

    3

    h-index

  2. IET Wireless Sensor Systems

    1 publications · 24 citations

    1

    h-index

  3. 1

    h-index

  4. 1

    h-index

  5. 1

    h-index

1–5