Use of Artificial Intelligence, Internet of Things, and Edge Intelligence in Long-Term Care for Older People: Comprehensive Analysis Through Bibliometric, Google Trends, and Content Analysis

AI, IoT, and EI collectively form a powerful ecosystem in LTC settings, addressing different aspects of care for older adults. Our study suggests that increased international collaboration and the integration of emerging themes such as "rehabilitation," "stroke," and "mHealth" are necessary to meet the evolving care needs of this population. Additionally, incorporating high-interest keywords such as "machine learning," "smart home," and "caregiver" can enhance discoverability and relevance for both academic and public audiences. Future research should focus on expanding sample sizes, conducting long-term multicenter trials, and exploring broader health conditions beyond dementia, such as frailty and depression.

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Publication Details

Journal
Journal of Medical Internet Research
Published
2025-03-04
DOI
https://doi.org/10.2196/56692
Citations
8
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
5.23
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article

Use of Artificial Intelligence, Internet of Things, and Edge Intelligence in Long-Term Care for Older People: Comprehensive Analysis Through Bibliometric, Google Trends, and Content Analysis

I‐Chien Wu, Chia-Chun Liu, Hung‐Yi Chiou, Yu‐Hung Chang et al.
8 citations
Journal of Medical Internet Research
Artificial Intelligence in Healthcare and Education
5.23
article

Use of Artificial Intelligence, Internet of Things, and Edge Intelligence in Long-Term Care for Older People: Comprehensive Analysis Through Bibliometric, Google Trends, and Content Analysis

I‐Chien Wu, Chia-Chun Liu, Hung‐Yi Chiou, Yu‐Hung Chang, Chia-Ming Yen, Chih‐Cheng Hsu, Ying‐Erh Chen, Ren‐Hua Chung, Shuo-Chen Chien, Tsung-En Yang, Hong-Ming Lin, Yu-Ping Hsiao, Xing Lü, Ping-Yen Yang
article en
8 citations

Abstract

AI, IoT, and EI collectively form a powerful ecosystem in LTC settings, addressing different aspects of care for older adults. Our study suggests that increased international collaboration and the integration of emerging themes such as "rehabilitation," "stroke," and "mHealth" are necessary to meet the evolving care needs of this population. Additionally, incorporating high-interest keywords such as "machine learning," "smart home," and "caregiver" can enhance discoverability and relevance for both academic and public audiences. Future research should focus on expanding sample sizes, conducting long-term multicenter trials, and exploring broader health conditions beyond dementia, such as frailty and depression.

Journal of Medical Internet ResearchVol. 27
Tamkang University (TW), National Health Research Institutes (TW), China Medical University (TW), Taipei Medical University (TW)
Openalex Percentile: Top 5%
Artificial Intelligence in Healthcare and Education
5.23
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