Innovative approach for online prediction of blood glucose profile in Type 1 diabetes patients

Giovanna Castillo Estrada, Harald Kirchsteiger, Luigi Del Re, Eric Renard

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

18 Citations (Scopus)

Abstract

Recursive identification techniques are used to estimate predictions for the human glucose-insulin subsystem. By replacing a constant gain with a physiologically inspired adaptation rule and adding as additional inputs the two variables ingested meal and administered insulin-which have the highest impact on the glucose concentration-the overall performance of a 45 min glucose prediction could be increased compared to standard identification and prediction methods. The results were analyzed from a system theoretical, and also from a clinical point of view using the CG-EGA.

Original languageEnglish
Title of host publicationProceedings of the 2010 American Control Conference, ACC 2010
PublisherIEEE Computer Society
Pages2015-2020
Number of pages6
ISBN (Print)9781424474264
DOIs
Publication statusPublished - 2010
Externally publishedYes

Publication series

NameProceedings of the 2010 American Control Conference, ACC 2010

Fingerprint

Dive into the research topics of 'Innovative approach for online prediction of blood glucose profile in Type 1 diabetes patients'. Together they form a unique fingerprint.

Cite this