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.

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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
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article

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

Guohui Hou, Zhixiong Zhou, Jinxi Zhang, Mohan Li et al.
22 citations
Journal of Medical Internet Research
Context-Aware Activity Recognition Systems
5.48
article

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

Guohui Hou, Zhixiong Zhou, Jinxi Zhang, Mohan Li, Zhen Li, Yu Liu, Jian Li, Hualong Qiu
article en
22 citations

Abstract

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.

Journal of Medical Internet ResearchVol. 26
Fujian Normal University (CN), Capital University of Physical Education and Sports (CN)
Openalex Percentile: Top 3%
Context-Aware Activity Recognition Systems
5.48
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