Extension of the Bergman Minimal Model for the Glucose-insulin Interaction


  • Levente Kovács


In this paper, the extension of the Bergman model (minimal model) is proposed with an internal insulin control (IIC) part, representing the own insulin control of the human body. The model has been verified with clinical experiments, by oral glucose intake tests. Employing parameter estimation, for inverse problem solution technique (SOSI - `single output single input´) was developed using Chebysev shifted polynomials, and linear identification in time domain based on measured glucose and insulin concentration values was applied. The glucose and insulin input functions have been approximated and the model parameters of IIC were estimated. This extended Bergman model suits considerably better to the practical clinical situation, and it can improve the effectivity of the external control design for glucose-insulin process. The IIC part has been identified via dynamical neural network using the proposed SOSI technique. The symbolic and numerical computations were carried out with Mathematica 5.1, and with its application Neural Networks 2.0.


Glucose-insulin interaction, internal insulin control, identification, dynamic neural network, symbolic computation, Mathematica.

How to Cite

Kovács, L. “Extension of the Bergman Minimal Model for the Glucose-insulin Interaction”, Periodica Polytechnica Electrical Engineering, 50(1-2), pp. 23–32, 2006.