Proceedings on Automation in Medical Engineering
Vol. 2 No. 1 (2023): Proc AUTOMED

Modelling tools and modelling concepts, ID 756

Parameter identification of a model describing the blood glucose metabolism using clinical data

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Carl-Friedrich Benner (RWTH Aachen University), Maria-Lenka Wolter (RWTH Aachen University), Maike van den Berg (RWTH Aachen University), Matthias Deininger (University Hospital Aachen), Thomas Breuer (University Hospital Aachen), Gernot Marx (University Hospital Aachen), Steffen Leonhardt (RWTH Aachen University), Marian Walter (RWTH Aachen University)


Models of the blood glucose metabolism in critically ill allow an enhanced understanding of the underlying pathology. Especially for the development of assisted insulin therapy the knowledge of the glucose dynamic is relevant. In modeling of blood glucose dynamic, identification of model parameters is a crucial step, also regarding personalized health care. Therefore, we present a workflow of parameter identification to obtain patient-specific model parameter and estimation of insulin sensitivity.

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