AI-enabled multimodal monitoring for enhanced safety and functional recovery in elderly and post-stroke care: A mixed-methods study

The AI-enabled multimodal monitoring system demonstrates significant clinical, economic, and quality-of-life benefits for elderly individuals and stroke survivors. The integrated approach outperforms single-modality systems and usual care across multiple outcome domains. Implementation success depends on leadership engagement, technical infrastructure readiness, comprehensive staff training, and ongoing user involvement in system configuration.

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Publication Details

Journal
Digital Health
Published
2025-05-01
DOI
https://doi.org/10.1177/20552076251384834
Citations
5
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
Field-Weighted Citation Impact
5.13
Controls
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article

AI-enabled multimodal monitoring for enhanced safety and functional recovery in elderly and post-stroke care: A mixed-methods study

Yanhua Zhao, Haytham F. Isleem, Aixu Duan, Wenxing Xue et al.
5 citations
Digital Health
Stroke Rehabilitation and Recovery
5.13
article

AI-enabled multimodal monitoring for enhanced safety and functional recovery in elderly and post-stroke care: A mixed-methods study

Yanhua Zhao, Haytham F. Isleem, Aixu Duan, Wenxing Xue, H. Zuo
article en
5 citations

Abstract

The AI-enabled multimodal monitoring system demonstrates significant clinical, economic, and quality-of-life benefits for elderly individuals and stroke survivors. The integrated approach outperforms single-modality systems and usual care across multiple outcome domains. Implementation success depends on leadership engagement, technical infrastructure readiness, comprehensive staff training, and ongoing user involvement in system configuration.

Digital HealthVol. 11
University of York (GB), Shanxi Datong University (CN)
Openalex Percentile: Top 5%
Stroke Rehabilitation and Recovery
5.13
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