An Effective Deep Learning Framework for Fall Detection: Model Development and Study Design
This study demonstrates that the DSCS model can significantly improve the accuracy of fall detection on 2 publicly available data sets and performs robustly in practical validation.
Authors
- Guohui Hou (ORCID: https://orcid.org/0000-0001-7744-1064)
- Zhixiong Zhou (ORCID: https://orcid.org/0000-0003-3369-1429)
- Jinxi Zhang (ORCID: https://orcid.org/0000-0002-8048-6703)
- Mohan Li (ORCID: https://orcid.org/0009-0005-3625-9801)
- Zhen Li (ORCID: https://orcid.org/0000-0002-1432-7472)
- Yu Liu (ORCID: https://orcid.org/0009-0006-7055-6524)
- Jian Li (ORCID: https://orcid.org/0009-0008-4413-9393)
- Hualong Qiu
Institutions
- Fujian Normal University (CN)
- Capital University of Physical Education and Sports (CN)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2024-08-05
- DOI
- https://doi.org/10.2196/56750
- Citations
- 22
- Primary Topic
- Context-Aware Activity Recognition Systems
- Type
- article
- Field-Weighted Citation Impact
- 5.48