Please use this identifier to cite or link to this item:
Title: Blood glucose level neural model for type 1 diabetes mellitus patients
Author: Alanis, A.Y.
Leon, B.S.
Sanchez, E.N.
Ruiz-Velazquez, E.
Issue Date: 2011
Abstract: This paper deals with the blood glucose level modeling for Type 1 Diabetes Mellitus (T1DM) patients. The model is developed using a recurrent neural network trained with an extended Kalman filter based algorithm in order to develop an affine model, which captures the nonlinear behavior of the blood glucose metabolism. The goal is to derive a dynamical mathematical model for the T1DM as the response of a patient to meal and subcutaneous insulin infusion. Experimental data given by continuous glucose monitoring system is utilized for identification and for testing the applicability of the proposed scheme to T1DM subjects. � 2011 World Scientific Publishing Company.
Appears in Collections:Producción científica UdeG

Files in This Item:
There are no files associated with this item.

Items in RIUdeG are protected by copyright, with all rights reserved, unless otherwise indicated.