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Context-aware early warning system for in-home healthcare using internet-of-things
KTH, Skolan för informations- och kommunikationsteknik (ICT), Industriell och Medicinsk Elektronik. University of Turku, Finland.ORCID-id: 0000-0001-8750-8242
KTH, Skolan för informations- och kommunikationsteknik (ICT), Industriell och Medicinsk Elektronik. University of Turku, Finland.
2016 (engelsk)Inngår i: 2nd International Summit on Internet of Things, IoT 360° 2015, Springer, 2016, s. 517-522Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Early warning score (EWS) is a prediction method to notify caregivers at a hospital about the deterioration of a patient. Deterioration can be identified by detecting abnormalities in patient’s vital signs several hours prior the condition of the patient gets life-threatening. In the existing EWS systems, monitoring of patient’s vital signs and the determining the score is mostly performed in a paper and pen based way. Furthermore, currently it is done solely in a hospital environment. In this paper, we propose to import this system to patients’ home to provide an automated platform which not only monitors patents’ vital signs but also looks over his/her activities and the surrounding environment. Thanks to the Internet-of-Things technology, we present an intelligent early warning method to remotely monitor in-home patients and generate alerts in case of different medical emergencies or radical changes in condition of the patient. We also demonstrate an early warning score analysis system which continuously performs sensing, transferring, and recording vital signs, activity-related data, and environmental parameters.

sted, utgiver, år, opplag, sider
Springer, 2016. s. 517-522
Emneord [en]
E-Health, Early warning score, Internet-of-things, Remote patient monitoring, Deterioration, Hospitals, Patient monitoring, E health, Early Warning System, Early-warning method, Environmental parameter, Hospital environment, Internet of things technologies, Surrounding environment, Internet of things
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Identifikatorer
URN: urn:nbn:se:kth:diva-201996DOI: 10.1007/978-3-319-47063-4_56ISI: 000398616500056Scopus ID: 2-s2.0-85000814878ISBN: 9783319470627 (tryckt)OAI: oai:DiVA.org:kth-201996DiVA, id: diva2:1077051
Konferanse
27 October 2015 through 29 October 2015
Merknad

QC 20170224

Tilgjengelig fra: 2017-02-24 Laget: 2017-02-24 Sist oppdatert: 2017-04-28bibliografisk kontrollert

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Rahmani, Amir-MohammadTenhunen, Hannu

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