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Neural network modeling and control of type 1 diabetes mellitus

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Abstract

This paper presents a developed and validated dynamic simulation model of type 1 diabetes, that simulates the progression of the disease and the two term controller that is responsible for the insulin released to stabilize the glucose level. The modeling and simulation of type 1 diabetes mellitus is based on an artificial neural network approach. The methodology builds upon an existing rich database on the progression of type 1 diabetes for a group of diabetic patients. The model was found to perform well at estimating the next glucose level over time without control. A neural controller that mimics the pancreas secretion of insulin into the body was also developed. This controller is of the two term type: one stage is responsible for short-term and the other for mid-term insulin delivery. It was found that the controller designed predicts an adequate amount of insulin that should be delivered into the body to obtain a normalization of the elevated glucose level. This helps to achieve the main objective of insulin therapy: to obtain an accurate estimate of the amount of insulin to be delivered in order to compensate for the increase in glucose concentration.

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  1. MIEE, Alisra University, Amman, Jordan

    A. Karim El-Jabali

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  1. A. Karim El-Jabali
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Correspondence to A. Karim El-Jabali.

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El-Jabali, A.K. Neural network modeling and control of type 1 diabetes mellitus. Bioprocess Biosyst Eng 27, 75–79 (2005). https://doi.org/10.1007/s00449-004-0363-3

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  • DOI: https://doi.org/10.1007/s00449-004-0363-3

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