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Clinically-validated technologies for assisted living

Spinsante, Susanna, Poli, Angelica, Batalla, Jordi Mongay, Krawiec, Piotr, Dobre, Ciprian, Bajenaru, Lidia, Mavromoustakis, Constandinos X., Constantinou, Costas S., Molan, Gregor, Herghelegiu, Anna Marie, Prada, Gabriel Ioan, Draghici, Rozeta and González-Vélez, Horacio (2023) Clinically-validated technologies for assisted living. Journal of Ambient Intelligence and Humanized Computing, 14 (3). pp. 2095-2116. ISSN 1868-5145

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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.

Item Type: Article
Additional Information: This article is licensed under a Creative Commons Attribution 4.0 International License.
Subjects: Q Science > QP Physiology
T Technology > T Technology (General) > Information Technology > Cloud computing
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > Computer networks > Internet of things
Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions: School of Computing > Staff Research and Publications
Depositing User: Tamara Malone
Date Deposited: 30 Mar 2023 11:34
Last Modified: 30 Mar 2023 11:50

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