Clinically-validated technologies for assisted living
One of the most important lifestyle risk factors for many chronic conditions in the older age, low physical activity has shown to have significant impact on the sustainability of national welfare in many developed countries. Technology-based assisted living solutions can effectively be used to enabl...
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Veröffentlicht in: | Journal of ambient intelligence and humanized computing 2023-03, Vol.14 (3), p.2095-2116 |
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creator | Spinsante, Susanna Poli, Angelica Mongay Batalla, Jordi Krawiec, Piotr Dobre, Ciprian Bǎjenaru, Lidia Mavromoustakis, Constandinos X Costantinou, Costas S Molan, Gregor Herghelegiu, Anna Marie Prada, Gabriel Ioan Drǎghici, Rozeta González–Vélez, Horacio |
description | One of the most important lifestyle risk factors for many chronic conditions in the older age, low physical activity has shown to have significant impact on the sustainability of national welfare in many developed countries. Technology-based assisted living solutions can effectively be used to enable older adults to optimise their health-related quality of life, as well as to promote an active and healthy longevity. This paper describes vINCI—an interdisciplinary research project to actively support assisted living for older adults via state-of-the-art assistive technologies—which seamlessly deploys an ambient intelligence environment to integrate wearable devices, networking, software, and personalised services. It entails clinical validation and feedback at home and residential care facilities via a cloud microservices platform. Underpinned by blockchain technologies, multiple wearable devices, apps, and cameras securely capture the anonymised facets of different life events, whilst machine learning models create individualised user profiles to analyse any decrease in the perceived health-related quality of life typically associated with old age. Two controlled pilots are being conducted with 80 participants at older adult facilities in Romania and Cyprus. By incorporating clinical validation and feedback from specialised practitioners, the vINCI technologies enable older adults not only to self-evaluate their physical activity level, but also to change their behaviours and lifestyle in the long-term. |
doi_str_mv | 10.1007/s12652-021-03419-y |
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Technology-based assisted living solutions can effectively be used to enable older adults to optimise their health-related quality of life, as well as to promote an active and healthy longevity. This paper describes vINCI—an interdisciplinary research project to actively support assisted living for older adults via state-of-the-art assistive technologies—which seamlessly deploys an ambient intelligence environment to integrate wearable devices, networking, software, and personalised services. It entails clinical validation and feedback at home and residential care facilities via a cloud microservices platform. Underpinned by blockchain technologies, multiple wearable devices, apps, and cameras securely capture the anonymised facets of different life events, whilst machine learning models create individualised user profiles to analyse any decrease in the perceived health-related quality of life typically associated with old age. Two controlled pilots are being conducted with 80 participants at older adult facilities in Romania and Cyprus. By incorporating clinical validation and feedback from specialised practitioners, the vINCI technologies enable older adults not only to self-evaluate their physical activity level, but also to change their behaviours and lifestyle in the long-term.</description><identifier>ISSN: 1868-5137</identifier><identifier>EISSN: 1868-5145</identifier><identifier>DOI: 10.1007/s12652-021-03419-y</identifier><language>eng</language><publisher>Heidelberg: Springer Nature B.V</publisher><subject>Adults ; Age ; Aging ; Ambient intelligence ; Automation ; Cardiovascular disease ; Chronic conditions ; Cryptography ; Developed countries ; Feedback ; Intelligence ; Interdisciplinary research ; Interdisciplinary studies ; Internet of Things ; Machine learning ; Older people ; Quality of life ; Research projects ; Risk factors ; Wearable technology</subject><ispartof>Journal of ambient intelligence and humanized computing, 2023-03, Vol.14 (3), p.2095-2116</ispartof><rights>The Author(s) 2021. 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Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c121y-3eced9951a375e0f84c85344aaf664eb3c75063a80e1f62c159aff9186b40d343</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2919463952?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,21388,27924,27925,33744,43805,64385,64389,72469</link.rule.ids></links><search><creatorcontrib>Spinsante, Susanna</creatorcontrib><creatorcontrib>Poli, Angelica</creatorcontrib><creatorcontrib>Mongay Batalla, Jordi</creatorcontrib><creatorcontrib>Krawiec, Piotr</creatorcontrib><creatorcontrib>Dobre, Ciprian</creatorcontrib><creatorcontrib>Bǎjenaru, Lidia</creatorcontrib><creatorcontrib>Mavromoustakis, Constandinos X</creatorcontrib><creatorcontrib>Costantinou, Costas S</creatorcontrib><creatorcontrib>Molan, Gregor</creatorcontrib><creatorcontrib>Herghelegiu, Anna Marie</creatorcontrib><creatorcontrib>Prada, Gabriel Ioan</creatorcontrib><creatorcontrib>Drǎghici, Rozeta</creatorcontrib><creatorcontrib>González–Vélez, Horacio</creatorcontrib><title>Clinically-validated technologies for assisted living</title><title>Journal of ambient intelligence and humanized computing</title><description>One of the most important lifestyle risk factors for many chronic conditions in the older age, low physical activity has shown to have significant impact on the sustainability of national welfare in many developed countries. Technology-based assisted living solutions can effectively be used to enable older adults to optimise their health-related quality of life, as well as to promote an active and healthy longevity. This paper describes vINCI—an interdisciplinary research project to actively support assisted living for older adults via state-of-the-art assistive technologies—which seamlessly deploys an ambient intelligence environment to integrate wearable devices, networking, software, and personalised services. It entails clinical validation and feedback at home and residential care facilities via a cloud microservices platform. Underpinned by blockchain technologies, multiple wearable devices, apps, and cameras securely capture the anonymised facets of different life events, whilst machine learning models create individualised user profiles to analyse any decrease in the perceived health-related quality of life typically associated with old age. Two controlled pilots are being conducted with 80 participants at older adult facilities in Romania and Cyprus. By incorporating clinical validation and feedback from specialised practitioners, the vINCI technologies enable older adults not only to self-evaluate their physical activity level, but also to change their behaviours and lifestyle in the long-term.</description><subject>Adults</subject><subject>Age</subject><subject>Aging</subject><subject>Ambient intelligence</subject><subject>Automation</subject><subject>Cardiovascular disease</subject><subject>Chronic conditions</subject><subject>Cryptography</subject><subject>Developed countries</subject><subject>Feedback</subject><subject>Intelligence</subject><subject>Interdisciplinary research</subject><subject>Interdisciplinary studies</subject><subject>Internet of Things</subject><subject>Machine learning</subject><subject>Older people</subject><subject>Quality of life</subject><subject>Research projects</subject><subject>Risk factors</subject><subject>Wearable technology</subject><issn>1868-5137</issn><issn>1868-5145</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNo9jk9LAzEUxIMoWNp-AU8LnqN5eUk2OcriPyh4seeSZl9qStjVzbaw394VxbnMwA9mhrEbEHcgRH1fQBotuZDABSpwfLpgC7DGcg1KX_5nrK_ZupSjmIUOAWDBdJNTl4LPeeJnn1PrR2qrkcJH1-f-kKhUsR8qX0oqPySnc-oOK3YVfS60_vMl2z49vjcvfPP2_No8bHgACRNHCtQ6p8FjrUlEq4LVqJT30RhFewy1Fga9FQTRyADa-RjdfHevRIsKl-z2t_dz6L9OVMbdsT8N3Ty5kw6cMui0xG_h40jN</recordid><startdate>20230301</startdate><enddate>20230301</enddate><creator>Spinsante, Susanna</creator><creator>Poli, Angelica</creator><creator>Mongay Batalla, Jordi</creator><creator>Krawiec, Piotr</creator><creator>Dobre, Ciprian</creator><creator>Bǎjenaru, Lidia</creator><creator>Mavromoustakis, Constandinos X</creator><creator>Costantinou, Costas S</creator><creator>Molan, Gregor</creator><creator>Herghelegiu, Anna Marie</creator><creator>Prada, Gabriel Ioan</creator><creator>Drǎghici, Rozeta</creator><creator>González–Vélez, Horacio</creator><general>Springer Nature B.V</general><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>20230301</creationdate><title>Clinically-validated technologies for assisted living</title><author>Spinsante, Susanna ; 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subjects | Adults Age Aging Ambient intelligence Automation Cardiovascular disease Chronic conditions Cryptography Developed countries Feedback Intelligence Interdisciplinary research Interdisciplinary studies Internet of Things Machine learning Older people Quality of life Research projects Risk factors Wearable technology |
title | Clinically-validated technologies for assisted living |
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