Direct continuous time system identification of MISO transfer function models applied to type 1 diabetes

This paper shows an application of continuous time system identification methods to Type 1 diabetes. First, a general MISO transfer function structure with individual nominator and denominator polynomials for each input is assumed and a parameter estimation procedure via an iterative prediction error method presented. Then, the proposed identification method is evaluated on a simple simulation example and finally applied on real-life data from Type 1 diabetes patients with the purpose of modeling blood glucose dynamics. To this aim, the method was extended to consider the time-varying nature of the system.