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dc.contributor.authorKölle, Konstanze
dc.contributor.authorFougner, Anders Lyngvi
dc.contributor.authorUnstad, Karl Arthur Frelsøy
dc.contributor.authorStavdahl, Øyvind
dc.date.accessioned2019-01-28T12:25:16Z
dc.date.available2019-01-28T12:25:16Z
dc.date.created2018-09-19T08:37:28Z
dc.date.issued2018
dc.identifier.issn2405-8963
dc.identifier.urihttp://hdl.handle.net/11250/2582624
dc.description.abstractPeople with diabetes mellitus type 1 could benefit from fully automated systems for glucose control. However, faults in any component of the system can severely compromise the safety of the user. An increasing degree of automation also increases the risk that faults remain undiscovered for longer periods - unless automated routines for fault detection are implemented at the same time. The aim of this article is to give a categorized overview of methods for fault detection in glucose control systems. This overview targets at disclosing hidden potentials for improvement and unresolved issues. Methods for fault detection in glucose control systems have been reviewed and classified with respect to categories such as the type of method and the exploited data basis. Both journal and conference papers were taken into account. Compared to the number of studies on glucose control algorithms, only a few articles have been published on fault detection. Surprisingly few of them consider system information beyond the standard diabetes care data.nb_NO
dc.language.isoengnb_NO
dc.publisherInternational Federation of Automatic Control (IFAC)nb_NO
dc.titleFault detection in glucose control: Is it time to move beyond CGM data?nb_NO
dc.title.alternativeFault detection in glucose control: Is it time to move beyond CGM data?nb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.pagenumber180-185nb_NO
dc.source.volume51nb_NO
dc.source.journalIFAC-PapersOnLinenb_NO
dc.source.issue27nb_NO
dc.identifier.doi10.1016/j.ifacol.2018.11.646
dc.identifier.cristin1610826
dc.relation.projectSamarbeidsorganet mellom Helse Midt-Norge og NTNU: 46075403nb_NO
dc.relation.projectNorges forskningsråd: 248872nb_NO
dc.description.localcode© 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd.nb_NO
cristin.unitcode194,63,25,0
cristin.unitnameInstitutt for teknisk kybernetikk
cristin.ispublishedfalse
cristin.fulltextpreprint
cristin.qualitycode1


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