Modeling of the Human Cardiovascular System for Detection of Atherosclerosis

Abstract Atherosclerosis is a pathological condition that can eventually lead to a heart attack, a stroke or a peripheral vascular disease, depending upon its site of occurrence in the human arterial network. In this work, a third order non-linear model of the cardiovascular system is proposed to distinguish between the healthy dynamics and the aforementioned pathological condition. An electrical equivalent of the cardiovascular system is presented with emphasis on systemic circulation and the model equations are derived using circuit theory concepts. The parameters are estimated using non-linear least squares estimation technique that minimizes the error between the modeled arterial blood pressure and the actual measurement data. The model has been tested on ten healthy subjects and five moderately high blood-pressure subjects. Two of the model parameters, namely, arterial compliance and peak cardiac elastance are proposed as indices of atherosclerosis. It has been shown that it is possible to distinguish between healthy and diseased subjects using these two estimated parameters.