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

Mobile Health (mhealth) (2939) Artificial Intelligence (1371) Falls and Emergency Detection with Sensors and other Technologies (36) Falls Prevention in the Elderly (69) New Methods (944) Wearable Devices and Sensors (888) Machine Learning (49) Machine Learning (1465)

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 Tweetations Metrics

Jinxi Zhang   1, 2 , PhD ;   Zhen Li   3 , PhD ;   Yu Liu   4 , MS ;   Jian Li   4 , MS ;   Hualong Qiu   4 , MS ;   Mohan Li   4 , MS ;   Guohui Hou   5, 6 , MS ;   Zhixiong Zhou   2 , PhD

1 Beijing Kupei Sports Culture Corporation Limited, Beijing, China

2 Institute of Artificial Intelligence in Sports, Capital University of Physical Education and Sports, Beijing, China

3 School of Physical Education and Sport Science, Fujian Normal University, Fuzhou, China

4 Institute for Sport Performance and Health Promotion, Capital University of Physical Education and Sports, Beijing, China

5 Bioelectronics Center of YZW, Shanghai, China

6 Walt Technology Group Co, Ltd, Jiaxing, China

Corresponding Author:

  • Zhixiong Zhou, PhD
  • Institute of Artificial Intelligence in Sports
  • Capital University of Physical Education and Sports
  • 11 North Third Ring West Road
  • Haidian District
  • Beijing, 100191
  • China
  • Phone: 86 13552505679
  • Email: zhouzhixiong@cupes.edu.cn