Title :
Innovative approach for online prediction of blood glucose profile in type 1 diabetes patients
Author :
Estrada, G.C. ; Kirchsteiger, H. ; del Re, L. ; Renard, E.
Author_Institution :
Inst. for Design & Control of Mechatronical Syst., Johannes Kepler Univ., Linz, Austria
fDate :
June 30 2010-July 2 2010
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.
Keywords :
biochemistry; biology computing; blood; diseases; physiological models; blood glucose profile; glucose concentration; human glucose-insulin subsystem; innovative approach; online prediction; physiologically inspired adaptation rule; recursive identification techniques; time 45 min; type 1 diabetes; Autoregressive processes; Blood; Diabetes; Europe; History; Insulin; Patient monitoring; Performance gain; Predictive models; Sugar;
Conference_Titel :
American Control Conference (ACC), 2010
Conference_Location :
Baltimore, MD
Print_ISBN :
978-1-4244-7426-4
DOI :
10.1109/ACC.2010.5531630