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dc.contributor.authorBennasar, M
dc.contributor.authorMcCormick, C
dc.contributor.authorPrice, B
dc.contributor.authorGooch, D
dc.contributor.authorStuart, A
dc.contributor.authorMehta, V
dc.contributor.authorClare, L
dc.contributor.authorBennaceur, A
dc.contributor.authorCohen, J
dc.contributor.authorBandara, A
dc.contributor.authorLevine, M
dc.contributor.authorNuseibeh, B
dc.date.accessioned2019-05-21T12:17:07Z
dc.date.issued2019-06-06
dc.description.abstractThe population of older adults is increasing across the globe; this growth is predicted to continue into the future. Most older adults prefer to live in their own home, but many live alone without immediate support. Living longer is often coupled with health and social problems and difficulty managing daily activities. Therefore, some level of care is required, but this is costly. Technological solutions may help to mitigate these problems by recognising subtle changes early and intervening before problems become unmanageable. Understanding a person’s usual behaviour when carrying out Activities of Daily Living (ADL) makes it possible to detect and respond to anomalies. However, current commercial and research monitoring systems do not offer an analysis of ADL and are unable to detect subtle changes. To address this gap, we propose the STRETCH (Socio-Technical Resilience for Enhancing Targeted Community Healthcare) sensor platform that is comprised of non-invasive sensors and machine learning techniques to recognise changes and allow early interventions. The paper discusses design principles, modalities, system architecture, and sensor network architecture.en_GB
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC)en_GB
dc.identifier.citationIn: Innovation in Medicine and Healthcare Systems, and Multimedia: Proceedings of KES-InMed-19 and KES-IIMSS-19 Conferences, edited by YW Chen, A Zimmermann, R Howlett, and L Jain, pp. 125-135.en_GB
dc.identifier.doi10.1007/978-981-13-8566-7_12
dc.identifier.grantnumberEP/P01013X/1en_GB
dc.identifier.grantnumberEP/R013144/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/37170
dc.language.isoenen_GB
dc.publisherSpringer Natureen_GB
dc.relation.urlhttps://www.springer.com/series/8767en_GB
dc.rights.embargoreasonUnder embargo until 06 June 2020 in compliance with publisher policy.en_GB
dc.rights© Springer Nature Singapore Pte Ltd. 2019.
dc.subjectSmart Houseen_GB
dc.subjectSensor Platformen_GB
dc.subjectOlder People careen_GB
dc.subjectAmbient Assisted livingen_GB
dc.subjecteHealthen_GB
dc.titleSTRETCH: a Sensor Platform for Non-Invasive Remote Monitoring of Older People in Real Timeen_GB
dc.typeConference paperen_GB
dc.date.available2019-05-21T12:17:07Z
dc.identifier.isbn9789811385650
dc.identifier.isbn9789811385667
dc.identifier.issn2190-3018
dc.descriptionThis is the author accepted manuscript. The final version is available from Springer via the DOI in this record.en_GB
dc.descriptionSmart Innovation, Systems and Technologies series, vol. 145.en_GB
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
dcterms.dateAccepted2019-04-27
exeter.funder::Engineering and Physical Sciences Research Council (EPSRC)en_GB
rioxxterms.funderEuropean Research Councilen_GB
rioxxterms.identifier.project291652en_GB
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2019-04-27
rioxxterms.typeConference Paper/Proceeding/Abstracten_GB
refterms.dateFCD2019-05-21T11:02:13Z
refterms.versionFCDAM
refterms.panelAen_GB
rioxxterms.funder.projectb6713ae5-64ca-4953-905d-934bba84e1c6en_GB


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