This paper is in the following e-collection/theme issue:

Mobile Health (mhealth) (3305) Artificial Intelligence (1928) Falls and Emergency Detection with Sensors and other Technologies (50) Falls Prevention in the Elderly (92) New Methods (1077) Wearable Devices and Sensors (1059) Machine Learning (1896)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/56750, first published .
An Effective Deep Learning Framework for Fall Detection: Model Development and Study Design

An Effective Deep Learning Framework for Fall Detection: Model Development and Study Design

An Effective Deep Learning Framework for Fall Detection: Model Development and Study Design

Authors of this article:

Jinxi Zhang1, 2 Author Orcid Image ;   Zhen Li3 Author Orcid Image ;   Yu Liu4 Author Orcid Image ;   Jian Li4 Author Orcid Image ;   Hualong Qiu4 Author Orcid Image ;   Mohan Li4 Author Orcid Image ;   Guohui Hou5, 6 Author Orcid Image ;   Zhixiong Zhou2 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

Journals

  1. Li Y, Liu P, Fang Y, Wu X, Xie Y, Xu Z, Ren H, Jing F. A Decade of Progress in Wearable Sensors for Fall Detection (2015–2024): A Network-Based Visualization Review. Sensors 2025;25(7):2205 View
  2. Inturi A, Manikandan V, Hu Y. Technical insights into vision-based fall detection systems: performances, challenges, and constraints. AI & SOCIETY 2025 View
  3. J. S, L. A. An explainable artificial intelligence driven fall system for sensor data analysis enhanced by butterworth filtering. Engineering Applications of Artificial Intelligence 2025;144:111364 View
  4. Sun Y, Chen J, Ji M, Li X. Wearable Technologies for Health Promotion and Disease Prevention in Older Adults: Systematic Scoping Review and Evidence Map. Journal of Medical Internet Research 2025;27:e69077 View