Sriyani Padmalatha Konara Mudiyanselage, Ching Teng Yao, Sujeewa Dilhani Maithreepala, Bih O Lee
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Data were extracted and categorized based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines.</p><p><strong>Results: </strong>A total of 73 studies met the inclusion criteria. Four main categories of fall detection technologies were identified: motion and sensor technologies, imaging and visual systems, environmental sensors, and robotic and autonomous systems. Commonly used devices: wearable accelerometers, gyroscopes, infrared array sensors, and smart carpet pressure sensors. Data storage methods were wearable devices, cameras, and floor-mounted sensors. Communication technologies included Bluetooth, Wi-Fi, and GPS, and notification methods ranged from alarms and SMS to cloud communications. Various health care response teams, including caregivers, health care providers, and emergency services, were integral to the fall detection systems.</p><p><strong>Conclusions and implications: </strong>Most studies primarily focus on fall detection; however, we recommend further clinical research to emphasize both fall detection and, more importantly, fall prevention (both primary and secondary). Investigating the effectiveness of fall prevention technologies in real-world settings will be crucial for enhancing the safety and quality of life of the aging population.</p>","PeriodicalId":17180,"journal":{"name":"Journal of the American Medical Directors Association","volume":null,"pages":null},"PeriodicalIF":4.2000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Emerging Digital Technologies Used for Fall Detection in Older Adults in Aged Care: A Scoping Review.\",\"authors\":\"Sriyani Padmalatha Konara Mudiyanselage, Ching Teng Yao, Sujeewa Dilhani Maithreepala, Bih O Lee\",\"doi\":\"10.1016/j.jamda.2024.105330\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To explore a comprehensive overview of digital technologies used for fall detection in older adults, categorizing the types, functions, and usability of these systems.</p><p><strong>Design: </strong>A scoping review was conducted to search across 5 databases (Embase, Medline [OVID], CINAHL, Coherence and IEEE Explore) from January 2013 to September 2023.</p><p><strong>Setting and participants: </strong>Studies in older adults living in nursing homes, care homes, residential homes, respite care homes, and all skilled and ambulatory care facilities (without context restrictions).</p><p><strong>Methods: </strong>This review followed the 6 methodological stages: (1) identification of research question; (2) identification of relevant studies; (3) study selection; (4) charting the data; (5) collating, summarizing, and reporting the results; and an optional stage, (6) consulting with stakeholders regarding findings to explore pivotal concepts in emerging technology usage in long-term care for falls detection among older people. Data were extracted and categorized based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines.</p><p><strong>Results: </strong>A total of 73 studies met the inclusion criteria. Four main categories of fall detection technologies were identified: motion and sensor technologies, imaging and visual systems, environmental sensors, and robotic and autonomous systems. Commonly used devices: wearable accelerometers, gyroscopes, infrared array sensors, and smart carpet pressure sensors. Data storage methods were wearable devices, cameras, and floor-mounted sensors. Communication technologies included Bluetooth, Wi-Fi, and GPS, and notification methods ranged from alarms and SMS to cloud communications. Various health care response teams, including caregivers, health care providers, and emergency services, were integral to the fall detection systems.</p><p><strong>Conclusions and implications: </strong>Most studies primarily focus on fall detection; however, we recommend further clinical research to emphasize both fall detection and, more importantly, fall prevention (both primary and secondary). 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Emerging Digital Technologies Used for Fall Detection in Older Adults in Aged Care: A Scoping Review.
Objective: To explore a comprehensive overview of digital technologies used for fall detection in older adults, categorizing the types, functions, and usability of these systems.
Design: A scoping review was conducted to search across 5 databases (Embase, Medline [OVID], CINAHL, Coherence and IEEE Explore) from January 2013 to September 2023.
Setting and participants: Studies in older adults living in nursing homes, care homes, residential homes, respite care homes, and all skilled and ambulatory care facilities (without context restrictions).
Methods: This review followed the 6 methodological stages: (1) identification of research question; (2) identification of relevant studies; (3) study selection; (4) charting the data; (5) collating, summarizing, and reporting the results; and an optional stage, (6) consulting with stakeholders regarding findings to explore pivotal concepts in emerging technology usage in long-term care for falls detection among older people. Data were extracted and categorized based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines.
Results: A total of 73 studies met the inclusion criteria. Four main categories of fall detection technologies were identified: motion and sensor technologies, imaging and visual systems, environmental sensors, and robotic and autonomous systems. Commonly used devices: wearable accelerometers, gyroscopes, infrared array sensors, and smart carpet pressure sensors. Data storage methods were wearable devices, cameras, and floor-mounted sensors. Communication technologies included Bluetooth, Wi-Fi, and GPS, and notification methods ranged from alarms and SMS to cloud communications. Various health care response teams, including caregivers, health care providers, and emergency services, were integral to the fall detection systems.
Conclusions and implications: Most studies primarily focus on fall detection; however, we recommend further clinical research to emphasize both fall detection and, more importantly, fall prevention (both primary and secondary). Investigating the effectiveness of fall prevention technologies in real-world settings will be crucial for enhancing the safety and quality of life of the aging population.
期刊介绍:
JAMDA, the official journal of AMDA - The Society for Post-Acute and Long-Term Care Medicine, is a leading peer-reviewed publication that offers practical information and research geared towards healthcare professionals in the post-acute and long-term care fields. It is also a valuable resource for policy-makers, organizational leaders, educators, and advocates.
The journal provides essential information for various healthcare professionals such as medical directors, attending physicians, nurses, consultant pharmacists, geriatric psychiatrists, nurse practitioners, physician assistants, physical and occupational therapists, social workers, and others involved in providing, overseeing, and promoting quality