Challenges in Data-based Patient Modeling for Glycemia Control in ICU-patients

T. Van Herpe, I. Goethals, B. Pluymers, F. De Smet, P. Wouters, G. Van den Berghe, and B. De Moor (B


Patient modeling, Intensive Care Unit, glycemia, ARX, PEM.


In this paper, we investigated the possibility of designing a system to control glycemia, i.e. the blood glucose concentration, in patients admitted in an Intensive Care Unit. The system consists of a patient model and a controller. This paper describes the first results of data based patient modeling. System theoretically, the identification problem was considered to be open-loop. Two input-output models were discussed: an AutoRegressive with eXogeneous inputs (ARX) and a Prediction-Error-Model (PEM). Glycemia simulations applied to a training set resulted in an acceptable performance. ARX-models outperformed PEM-models. However, the use of these models on a validation set was clinically not yet feasible due to large glycemia errors. Future research is needed to develop a more accurate patient model.

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