Finite Element Method based Modeling of a Sensory System for Detection of Atherosclerosis in Human Using Electrical Impedance Tomography

This paper presents a simulation based study on identification of atherosclerosis in human blood vessels through Electrical Impedance Tomography (EIT) technique. Atherosclerosis is a vital coronary disease in which plaque (a solid substance made of fat, cholesterol, calcium and other substances found in blood) builds up inside the arteries and can lead to serious problems, including heart attack, stroke, or even death. In this work, a non-invasive imaging technique based on the variation of electrical conductivity (and/or relative permittivity) values of the body tissues have been proposed for detection of atherosclerosis. Here, we have modeled the 2D structure of vessels within a closed specified environment. The 2D model is then transformed to 3D platform for analysis. The clots inside the blood vessels have varying electrical conductivities (and/or relative permittivity's) in comparison to that for the blood vessels. Thus, by maintaining a potential difference on the electrodes, which are placed on the body surface, the variation of potential field are obtained along a 2D plane by utilizing the forward solver problem of Electrical Impedance Tomography (EIT). The simulation model and their respective studies are performed in Finite Element Method based Multiphysics Software platform.