Modelling of fasting glucose-insulin dynamics from sparse data

Tinna Björk Aradóttir, Dimitri Boiroux, Henrik Bengtsson, Niels Kjølstad Poulsen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

260 Downloads (Pure)

Abstract

With the fast growth of diabetes prevalence, the disease is now considered an epidemic. Diabetes is characterized by elevated glucose levels, that may be treated with insulin. Tight control of glucose is essential for prevention of complications and patients’ well-being. In this paper we model the fasting glucose-insulin dynamics in type 2 diabetes, aiming at controlling the glucose level. Relevant clinical data are typically sparse and have a sampling period much greater than the fast dynamics in the glucose-insulin dynamics in humans. We adapt a physiological model such that important slow non-linear dynamics are identifiable and test the resulting model on deterministic simulated data and sparse, slow sampled clinical data.
Original languageEnglish
Title of host publicationProceedings of 40th International Conoference of the IEEE Engineering in Medicine and Biology Society
PublisherIEEE
Publication date2018
Pages2354-57
ISBN (Print)978-1-5386-3646-6
DOIs
Publication statusPublished - 2018
Event40th International Conoference of the IEEE Engineering in Medicine and Biology Society - Honolulu, United States
Duration: 17 Jul 201821 Jul 2018
https://embc.embs.org/2018/

Conference

Conference40th International Conoference of the IEEE Engineering in Medicine and Biology Society
CountryUnited States
CityHonolulu
Period17/07/201821/07/2018
Internet address

Fingerprint Dive into the research topics of 'Modelling of fasting glucose-insulin dynamics from sparse data'. Together they form a unique fingerprint.

Cite this