DYNAMIC MODEL DEVELOPMENT AND RECEDING HORIZON CONTROL OF BLOOD GLUCOSE CONCENTRATION

📄 Project Abstract

Biological systems usually consist of large number of components and involve processes at a variety of spatial, temporal and biological scales. This study presents a framework for model identification and the use of Global Sensitivity Analysis (GSA) in systems biology modelling and shows how the information content of clinical data from Short Insulin Tolerance Test (SITT) can be handled by optimal model-based estimation techniques. The goal is to identify dynamic model of type II diabetes and estimate a set of parameters of the model with greater accuracy and precision. Based on the SITT data, the blood glucose dynamic model was identified as a system of linear differential equation with constant coefficients (parameters). The sensitivity of the parameters was tested using a novel GSA based approach, and Derivative-Based Global Sensitivity Measures (DGSM). The proposed approach was implemented in SensSB (a Matlab based toolbox). For the purpose of comparison, the sensitivity of the mod...