International Journal of Neural Systems · 2011 · 20 citations · 43 references
MedicineEndocrinologyPharmacokineticsDiabetologyMetabolic RegulationPhysiological Systems ModelingBlood Glucose MonitoringContinuous Glucose MonitoringDiabetes MellitusGlycemic ControlMetabolism ModelingNeural System ModelingBlood Glucose RegulationContinuous Subcutaneous InfusionContinuous Subcutaneous Insulin InfusionExtended Kalman FilterGlucose MonitoringType 1 Diabetes ModelsType 1 Diabetes MonitoringType 1 Diabetes Pathophysiology
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.
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