ReviewRisk management and healthcare policy2026
Privacy, Security & Governance Frameworks for AI-Powered Wearable Internet of Health Things in Elderly Care: A Comprehensive Review.
Review in Risk management and healthcare policy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Voices from Primary Care: A Needs Assessment Among Multidisciplinary Primary-Care Teams for a Health Promotion Model-Based E-Counseling Platform to Support Fall Prevention Among Older Adults in Indonesia.Journal of multidisciplinary healthcare · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The global aging population is expanding at an unprecedented rate, with projections indicating that 1.4 billion people will be aged 60 years or older by 2030 and 2.1 billion by 2050, placing immense pressure on healthcare systems worldwide. Artificial intelligence (AI)-powered wearable Internet of Health Things (IoHT) devices - including smartwatches, biosensors, and continuous health monitors - have emerged as transformative tools for real-time elderly health monitoring, fall detection, and predictive analytics. However, the massive collection of sensitive biometric data by these devices raises critical concerns regarding privacy, security, and governance that remain insufficiently addressed, particularly for elderly populations. This comprehensive review synthesizes evidence from 333 peer-reviewed articles published between 2018 and 2025 cross PubMed, Scopus, Web of Science, IEEE Xplore, and Google Scholar to identify, analyze, and compare governance frameworks for AI-powered wearable IoHT in elderly care. The analysis reveals significant regulatory fragmentation across jurisdictions: while the European Union's General Data Protection Regulation (GDPR) and AI Act provide the most comprehensive rights-based framework, the United States relies on a patchwork of sector-specific regulations with notable gaps for consumer wearables, and Asia-Pacific nations exhibit highly variable approaches ranging from mature (Singapore, Japan) to nascent (Indonesia, Malaysia). Elderly-specific provisions remain conspicuously absent across all regulatory regimes examined. This review proposes a novel five-layer integrative governance framework - the first to unify technical security, privacy protection, ethical AI governance, regulatory compliance, and person-centered governance specifically designed for elderly care contexts. The framework addresses unique vulnerabilities associated with cognitive decline, reduced digital literacy, and caregiver dependency. Findings underscore the urgent need for harmonized, age-sensitive regulatory approaches and privacy-preserving technologies such as federated learning and differential privacy to ensure that AI-powered wearable IoHT fulfills its promise of enhancing elderly healthcare without compromising dignity, autonomy, or data security.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.