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Context-aware early warning system for in-home healthcare using internet-of-things
KTH, School of Information and Communication Technology (ICT), Industrial and Medical Electronics. University of Turku, Finland.ORCID iD: 0000-0001-8750-8242
KTH, School of Information and Communication Technology (ICT), Industrial and Medical Electronics. University of Turku, Finland.
2016 (English)In: 2nd International Summit on Internet of Things, IoT 360° 2015, Springer, 2016, 517-522 p.Conference paper, (Refereed)
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.

Place, publisher, year, edition, pages
Springer, 2016. 517-522 p.
Keyword [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
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:kth:diva-201996DOI: 10.1007/978-3-319-47063-4_56ISI: 000398616500056Scopus ID: 2-s2.0-85000814878ISBN: 9783319470627 (print)OAI: oai:DiVA.org:kth-201996DiVA: diva2:1077051
Conference
27 October 2015 through 29 October 2015
Note

QC 20170224

Available from: 2017-02-24 Created: 2017-02-24 Last updated: 2017-04-28Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf