• DocumentCode
    3295404
  • 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
  • fYear
    2010
  • fDate
    June 30 2010-July 2 2010
  • Firstpage
    2015
  • Lastpage
    2020
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2010
  • Conference_Location
    Baltimore, MD
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4244-7426-4
  • Type

    conf

  • DOI
    10.1109/ACC.2010.5531630
  • Filename
    5531630