ADAPTIVE MODELING FOR CONTROL OF GLYCEMIA IN CRITICALLY ILL PATIENTS

Autor:	Greet Van den Berghe, Bart De Moor, Niels Haverbeke, Marcelo Espinoza, Tom Van Herpe
Rok vydání:	2007
Předmět:	Engineering business.industry Estimation theory Critically ill Control (management) System identification General Medicine Kalman filter Machine learning computer.software_genre Model based control Model predictive control Control theory Artificial intelligence business computer
Zdroj:	Scopus-Elsevier
ISSN:	1474-6670
DOI:	10.3182/20070604-3-mx-2914.00029
Popis:	In this paper we propose an optimized adaptive ‘minimal’ modeling approach for predicting glycemia of critically ill patients and a corresponding Model based Predictive Control (MPC) setting for controlling glycemia. Re-estimations of the model, based on a real-life dataset from 19 critically ill patients, are performed every hour or every four hours by only considering recently passed data. The contributions of this study are the determination of the best dataset size for the re-estimations and the proposed MPC design. The results are satisfactory both in terms of forecasting ability and in qualitative controller performance.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed06b58b0f2d134606fdec5b31f0d3ad https://doi.org/10.3182/20070604-3-mx-2914.00029 Zobrazit plný text záznamu