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Mathematical models can be employed to simulate a patient’s individual physiology and can therefore be used to predict reactions to changes in the therapy. To be clinically useful, those models need to be identifiable from data available at the bedside. Gradient based methods to identify the values of the model parameters that represent the recorded data highly depend on the initial estimates. The proposed work implements a previously developed method to overcome those dependencies to identify a three parameter model of gas exchange. The proposed hierarchical method uses models of lower order related to the three parameter model to calculate valid initial estimates for the parameter identification. The presented approach was evaluated using 12 synthetic patients and compared to a traditional direct approach as well as a global search method. Results show that the direct approach is highly dependent on how well the initial estimates are selected, while the hierarchical approach was able to find correct parameter values in all tested patients.

Evaluating different approaches to identify a three parameter gas exchange model