TY - JOUR
T1 - Clinically-validated technologies for assisted living
T2 - The vINCI project
AU - Spinsante, Susanna
AU - Poli, Angelica
AU - Mongay Batalla, Jordi
AU - Krawiec, Piotr
AU - Dobre, Ciprian
AU - Bǎjenaru, Lidia
AU - Mavromoustakis, Constandinos X.
AU - Costantinou, Costas S.
AU - Molan, Gregor
AU - Herghelegiu, Anna Marie
AU - Prada, Gabriel Ioan
AU - Drǎghici, Rozeta
AU - González–Vélez, Horacio
N1 - Funding Information:
This article is based upon work from vINCI: “Clinically-validated INtegrated Support for Assistive Care and Lifestyle Improvement: the Human Link” https://vinci.ici.ro/ , a project funded by the Europen Union’s Active Assisted Living Programme under grant agreement AAL2017-63-vINCI.
Publisher Copyright:
© 2021, The Author(s).
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Ambient intelligence
KW - Assisted living
KW - Assistive technologies
KW - Blockchain
KW - Clinical validation
KW - Cloud computing
KW - IoT
KW - Machine Learning
KW - Older Adults
KW - Quality of Life
UR - http://www.scopus.com/inward/record.url?scp=85112544206&partnerID=8YFLogxK
U2 - 10.1007/s12652-021-03419-y
DO - 10.1007/s12652-021-03419-y
M3 - Article
AN - SCOPUS:85112544206
SN - 1868-5137
JO - Journal of Ambient Intelligence and Humanized Computing
JF - Journal of Ambient Intelligence and Humanized Computing
ER -