Tuning of Controller for Type 1 Diabetes Treatment with Stochastic Differential Equations

Anne Katrine Duun-Henriksen, Dimitri Boiroux, Signe Schmidt, Ole Skyggebjerg, Sten Madsbad, Peter Ruhdal Jensen, John Bagterp Jørgensen, Niels Kjølstad Poulsen, Kirsten Nørgaard, Henrik Madsen

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

319 Downloads (Pure)

Abstract

People with type 1 diabetes need several insulin injections every day to keep their blood glucose level in the normal range and thereby avoiding the acute and long term complications of diabetes. One of the recent treatments consists of a pump injecting insulin into the subcutaneous layer combined with a continuous glucose monitor (CGM) frequently observing the glucose level. Automatic control of the insulin pump based on CGM observations would ease the burden of constant diabetes treatment and management. We have developed a controller designed to keep the blood glucose level in the normal range by adjusting the size of insulin infusions from the pump based on model predictive control (MPC). A clinical pilot study to test the performance of the MPC controller overnight was performed. The conclusion was that the controller relied too much on the local trend of the blood glucose level which is a problem due to the noise corrupted observations from the CGM. In this paper we present a method to estimate the optimal Kalman gain in the controller based on stochastic differential equation modeling. With this model type we could estimate the process noise and observation noise separately based on data from the rst clinical pilot study. In doing so we obtained a more robust control algorithm which is less sensitive to
fluctuations in the CGM observations and rely more on the global physiological trend of the blood glucose level. Finally, we present the promising results from the second pilot study testing the improved controller.
Original languageEnglish
Title of host publicationBiological and Medical Systems
Volume8
Publication date2012
Pages46-51
ISBN (Print)978-3-902823-10-6
DOIs
Publication statusPublished - 2012
Event8th IFAC Symposium on Biological and Medical Systems - Budapest, Hungary
Duration: 29 Aug 201231 Aug 2012
http://bms.iit.bme.hu/

Conference

Conference8th IFAC Symposium on Biological and Medical Systems
CountryHungary
CityBudapest
Period29/08/201231/08/2012
Internet address
SeriesIFAC Proceedings Volumes (IFAC-PapersOnline)

Fingerprint Dive into the research topics of 'Tuning of Controller for Type 1 Diabetes Treatment with Stochastic Differential Equations'. Together they form a unique fingerprint.

Cite this