Andrew Chan, Joanne Cai, Linna Qian, Brendan Coutts, Steven Phan, Geoff Gregson, Michael Lipsett, Adriana M Ríos Rincón
{"title":"老年人远程家庭健康监测的家庭定位：系统综述。","authors":"Andrew Chan, Joanne Cai, Linna Qian, Brendan Coutts, Steven Phan, Geoff Gregson, Michael Lipsett, Adriana M Ríos Rincón","doi":"10.2196/57320","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p><p><strong>Trial registration: </strong>PROSPERO CRD42022339845; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=339845.</p>","PeriodicalId":36245,"journal":{"name":"JMIR Aging","volume":"7 ","pages":"e57320"},"PeriodicalIF":5.0000,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11661402/pdf/","citationCount":"0","resultStr":"{\"title\":\"In-Home Positioning for Remote Home Health Monitoring in Older Adults: Systematic Review.\",\"authors\":\"Andrew Chan, Joanne Cai, Linna Qian, Brendan Coutts, Steven Phan, Geoff Gregson, Michael Lipsett, Adriana M Ríos Rincón\",\"doi\":\"10.2196/57320\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p><p><strong>Trial registration: </strong>PROSPERO CRD42022339845; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=339845.</p>\",\"PeriodicalId\":36245,\"journal\":{\"name\":\"JMIR Aging\",\"volume\":\"7 \",\"pages\":\"e57320\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2024-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11661402/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JMIR Aging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2196/57320\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GERIATRICS & GERONTOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMIR Aging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2196/57320","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GERIATRICS & GERONTOLOGY","Score":null,"Total":0}
In-Home Positioning for Remote Home Health Monitoring in Older Adults: Systematic Review.
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.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
