Innovative Approach for Online Prediction of Blood Glucose Profile in Type 1 Diabetes Patients

被引：0

作者：

Estrada, Giovanna Castillo ^{[1
]}

Kirchsteiger, Harald ^{[1
]}

del Re, Luigi ^{[1
]}

Renard, Eric ^{[2
,3
]}

机构：

[1] Johannes Kepler Univ Linz, Inst Design & Control Mechatron Syst, A-4040 Linz, Austria

[2] Univ Hosp, Dept Endocrinol, Cleveland, OH 44106 USA

[3] Univ Montpellier I, Dept Endocrinol, Montpellier, France

来源：

2010 AMERICAN CONTROL CONFERENCE | 2010年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：2015 / 2020

页数：6

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