Author(s)

R. Gul & S. Bernhard

Abstract

Cardiovascular disease is one of the major problems in today’s medicine and the number of patients increase worldwide. To treat these types of diseases, prior knowledge about function and dysfunction of the cardiovascular systemis essential for identifying the disease in an early stage. Mathematical modeling is a powerful tool for prediction and investigation of the cardiovascular system. It has been shown, that theWindkessel model, drawing an analogy between electrical circuits and fluid flow, is an effective method to model the human cardiovascular system. The aims of this work are the derivation of a computational cardiovascular model for the arm arteries, and to analyze the behavior of the vascular network structure by parameter sensitivity analysis. Sensitivity analysis is essential for parameter estimation and simplification of cardiovascular models. In optimal experiment design (OED) sensitivity analysis is used to construct experiments and corresponding models that allow the interpretation of cardiovascular measurements in an effective manner. In this paper we have applied sensitivity analysis to a linear elastic model of the arm arteries to find sensitive parameters and their confidence intervals that guide us to the estimation of cardiovascular network parameters. To calculate the percentage effect on the measurable state variables pressure and flow, with respect to percentage change in cardiovascular input parameters, we use norms. This method allows us to quantify and verify results obtained by sensitivity analysis. The sensitivities with respect to flow resistance, arterial compliance and flow inertia, reveal that the flow resistance and diameter of the vessels are the most

Keywords

computational cardiovascular model, cardiovascular parameters, sensitivity analysis, Windkessel model