In-Home Positioning for Remote Home Health Monitoring in Older Adults: Systematic Review.

IF 5 Q1 GERIATRICS & GERONTOLOGY
JMIR Aging Pub Date : 2024-12-02 DOI:10.2196/57320
Andrew Chan, Joanne Cai, Linna Qian, Brendan Coutts, Steven Phan, Geoff Gregson, Michael Lipsett, Adriana M Ríos Rincón
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引用次数: 0

Abstract

Background: With the growing proportion of Canadians aged >65 years, smart home and health monitoring technologies may help older adults manage chronic disease and support aging in place. Localization technologies have been used to support the management of frailty and dementia by detecting activities in the home.

Objective: This systematic review aims to summarize the clinical evidence for in-home localization technologies, review the acceptability of monitoring, and summarize the range of technologies being used for in-home localization.

Methods: The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology was followed. MEDLINE, Embase, CINAHL, and Scopus were searched with 2 reviewers performing screening, extractions, and quality assessments.

Results: A total of 1935 articles were found, with 36 technology-focused articles and 10 articles that reported on patient outcomes being included. From moderate- to high-quality studies, 2 studies reported mixed results on identifying mild cognitive dementia or frailty, while 4 studies reported mixed results on the acceptability of localization technology. Technologies included ambient sensors; Bluetooth- or Wi-Fi-received signal strength; localizer tags using radio frequency identification, ultra-wideband, Zigbee, or GPS; and inertial measurement units with localizer tags.

Conclusions: The clinical utility of localization remains mixed, with in-home sensors not being able to differentiate between older adults with healthy cognition and older adults with mild cognitive impairment. However, frailty was detectable using in-home sensors. Acceptability is moderately positive, particularly with ambient sensors. Localization technologies can achieve room detection accuracies up to 92% and linear accuracies of up to 5-20 cm that may be promising for future clinical applications.

Trial registration: PROSPERO CRD42022339845; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=339845.

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来源期刊
JMIR Aging
JMIR Aging Social Sciences-Health (social science)
CiteScore
6.50
自引率
4.10%
发文量
71
审稿时长
12 weeks
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