Article ID Journal Published Year Pages File Type
718285 IFAC Proceedings Volumes 2012 5 Pages PDF
Abstract

Mathematical models can be exploited to simulate physiological processes in the human body as well as predict their reaction to changes in the therapy regime of a patient. Implementing these models in Medical Decision Support Systems (MDSS) can help in optimizing therapy settings. MDSS optimizing ventilation therapy in critically ill patients should not only consider respiratory mechanics but extend simulations to also consider other parts of the human body. A previously presented framework allows combination of three model families (respiratory mechanics, cardiovascular dynamics and gas exchange) to provide a broader picture when predicting the outcome of a therapy setting. The three model families are dynamically combined to form a complex model system with interacting submodels.The framework computes the combined submodels as a tightly coupled system, i.e. an applied solver algorithm chooses a step size to fit the submodel with highest system dynamics. Tests revealed that simulation time increases rapidly with rising system complexity, i.e. the number of differential equations defining the interacting model system. This is due to very expensive computing when detailed models of cardiovascular dynamics are included. However, this simulation detail is not necessary in all scenarios.Thus, a simplified cardiovascular model that is able to reproduce basic physiological behavior is introduced. This model consists only of difference equations and does not require special algorithms to be numerically solved. The model is based on the beat-to-beat model presented by DeBoer et al. and has been extended to react to intrathoracic pressure levels that are present during mechanical ventilation. To include sensitivity to mechanical ventilation, a 19-compartment model as proposed by Leaning et al. has been analyzed and model behavior has been implemented as a simple equation into the beat-to-beat model.Tests showed, that the model is able to closely represent general model behavior compared to the 19-compartment model. Blood pressures were calculated with a maximum deviation of 1.8%, leading to a simulation error of 1.7% in cardiac output. Combination with a gas exchange showed maximum simulation error of 0.4%. Therefore, the proposed model is able to be used in combinations where cardiovascular simulation does not have to be detailed. Computing costs have been decreased dramatically by factor 186 compared to a model combination employing the 19-compartment model.

Related Topics
Physical Sciences and Engineering Engineering Computational Mechanics