In silico comparison of continuous glucose monitor failure mode strategies for an artificial pancreas

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dc.contributor.authorLu, Yunjieen_NZ
dc.contributor.authorKoay, Abigailen_NZ
dc.contributor.authorMayo, Michaelen_NZ
dc.contributor.editorBach, K.en_NZ
dc.contributor.editorBunescu, R.en_NZ
dc.contributor.editorMarling, C.en_NZ
dc.contributor.editorWiratunga, N.en_NZ
dc.coverage.spatialSantiago de Compostela, Spain & Virtuallyen_NZ
dc.date.accessioned2020-10-05T21:59:22Z
dc.date.available2020-10-05T21:59:22Z
dc.date.issued2020en_NZ
dc.description.abstractAn artificial pancreas is a medical Internet of Thingsbased system consisting of a continuous glucose monitor, an insulin pump, and a micro-controller. The use of artificial pancreas systems is becoming increasingly popular amongst patients with type 1 diabetes due to its effective ability to allow the patient better control of his/her own blood glucose levels compared to other more standard treatments. In this paper, the problem of missing sensor readings in the glucose monitor data is considered. How should the microcontroller (which adjusts the insulin pump based on monitor readings) react when the glucose monitor stops transmitting for an unpredictable period of time? A strategy that answers this question is called a failure mode strategy. In this paper, several potential failure mode strategies are explored in the context of simulation experiments. Results are presented showing that at least one effective and simple failure mode strategy (0.5µ & LR<72) exists.
dc.format.mimetypeapplication/pdf
dc.identifier.citationLu, Y., Koay, A., & Mayo, M. (2020). In silico comparison of continuous glucose monitor failure mode strategies for an artificial pancreas. In K. Bach, R. Bunescu, C. Marling, & N. Wiratunga (Eds.), Proceedings of 5th International Workshop on Knowledge Discovery in Healthcare Data (KDH 2020) (Vol. 2675, pp. 53–57). Santiago de Compostela, Spain & Virtually: CEUR Workshop Proceedings.en
dc.identifier.issn1613-0073en_NZ
dc.identifier.urihttps://hdl.handle.net/10289/13870
dc.language.isoen
dc.publisherCEUR Workshop Proceedingsen_NZ
dc.relation.isPartOfProceedings of 5th International Workshop on Knowledge Discovery in Healthcare Data (KDH 2020)en_NZ
dc.relation.urihttp://ceur-ws.org/Vol-2675/paper8.pdfen_NZ
dc.rights© Copyright by the authors.
dc.sourceKDH 2020en_NZ
dc.subjectcomputer scienceen_NZ
dc.titleIn silico comparison of continuous glucose monitor failure mode strategies for an artificial pancreasen_NZ
dc.typeConference Contribution
pubs.begin-page53
pubs.elements-id257589
pubs.end-page57
pubs.finish-date2020-08-30en_NZ
pubs.organisational-group/Waikato
pubs.organisational-group/Waikato/2024 PBRF
pubs.organisational-group/Waikato/DHECS
pubs.organisational-group/Waikato/DHECS/2024 PBRF - DHEC
pubs.organisational-group/Waikato/DHECS/SCMS
pubs.organisational-group/Waikato/DHECS/SCMS/2024 PBRF - SCMS
pubs.start-date2020-08-29en_NZ
pubs.user.infoMayo, Michael (mmayo@waikato.ac.nz)
pubs.user.infoKoay, Abigail (akoay@waikato.ac.nz)
pubs.volume2675en_NZ
uow.verification.statusunverified
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