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dc.contributor.authorLopez Zazueta, Claudia
dc.contributor.authorStavdahl, Øyvind
dc.contributor.authorFougner, Anders Lyngvi
dc.date.accessioned2021-11-10T08:50:16Z
dc.date.available2021-11-10T08:50:16Z
dc.date.created2021-10-26T13:19:26Z
dc.date.issued2021
dc.identifier.issn0018-9294
dc.identifier.urihttps://hdl.handle.net/11250/2828822
dc.description.abstractObjective: The design of an Artificial Pancreas to regulate blood glucose levels requires reliable control methods. Model Predictive Control has emerged as a promising approach for glycemia control. However, model-based control methods require computationally simple and identifiable mathematical models that represent glucose dynamics accurately, which is challenging due to the complexity of glucose homeostasis. Methods: In this work, a simple model is deduced to estimate blood glucose concentration in subjects with Type 1 Diabetes Mellitus. Novel features in the model are power-law kinetics for intraperitoneal insulin absorption and a separate glucagon sensitivity state. Profile likelihood and a method based on singular value decomposition of the sensitivity matrix are carried out to assess parameter identifiability and guide a model reduction for improving the identification of parameters. Results: A reduced model with 10 parameters is obtained and calibrated, showing good fit to experimental data from pigs where insulin and glucagon boluses were delivered in the intraperitoneal cavity. Conclusion: A simple model with power-law kinetics can accurately represent glucose dynamics submitted to intraperitoneal insulin and glucagon injections. Importance: The parameters of the reduced model were not found to lack of local practical or structural identifiability.en_US
dc.language.isoengen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.subjectSystemidentifikasjonen_US
dc.subjectSystem identificationen_US
dc.subjectMatematisk modelleringen_US
dc.subjectMathematical modellingen_US
dc.subjectDiabetesen_US
dc.subjectDiabetesen_US
dc.subjectKunstig bukspyttkjertelen_US
dc.subjectArtificial Pancreasen_US
dc.titleLow-Order Nonlinear Animal Model of Glucose Dynamics for a Bihormonal Intraperitoneal Artificial Pancreasen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
dc.rights.holder© IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.subject.nsiVDP::Medisinsk teknologi: 620en_US
dc.subject.nsiVDP::Medical technology: 620en_US
dc.source.journalIEEE Transactions on Biomedical Engineeringen_US
dc.identifier.doi10.1109/TBME.2021.3125839
dc.identifier.cristin1948544
dc.relation.projectNorges forskningsråd: 248872en_US
cristin.ispublishedfalse
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cristin.qualitycode1


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