Open Science Research Excellence

Open Science Index

Commenced in January 2007 Frequency: Monthly Edition: International Paper Count: 2

2
3487
Obstacles as Switches between Different Cardiac Arrhythmias
Abstract:
Ventricular fibrillation is a very important health problem as is the cause of most of the sudden deaths in the world. Waves of electrical activity are sent by the SA node, propagate through the cardiac tissue and activate the mechanisms of cell contraction, and therefore are responsible to pump blood to the body harmonically. A spiral wave is an abnormal auto sustainable wave that is responsible of certain types of arrhythmias. When these waves break up, give rise to the fibrillation regime, in which there is a complete loss in the coordination of the contraction of the heart muscle. Interaction of spiral waves and obstacles is also of great importance as it is believed that the attachment of a spiral wave to an obstacle can provide with a transition of two different arrhythmias. An obstacle can be partially excitable or non excitable. In this talk, we present a numerical study of the interaction of meandering spiral waves with partially and non excitable obstacles and focus on the problem where the obstacle plays a fundamental role in the switch between different spiral regimes, which represent different arrhythmic regimes. Particularly, we study the phenomenon of destabilization of spiral waves due to the presence of obstacles, a phenomenon not completely understood (This work will appear as a Chapter in a Book named Cardiac Arrhytmias by INTECH under the name "Spiral Waves, Obstacles and Cardiac Arrhythmias", ISBN 979-953-307-050-5.).
1
11542
Involving Action Potential Morphology on a New Cellular Automata Model of Cardiac Action Potential Propagation
Abstract:
Computer modeling has played a unique role in understanding electrocardiography. Modeling and simulating cardiac action potential propagation is suitable for studying normal and pathological cardiac activation. This paper presents a 2-D Cellular Automata model for simulating action potential propagation in cardiac tissue. We demonstrate a novel algorithm in order to use minimum neighbors. This algorithm uses the summation of the excitability attributes of excited neighboring cells. We try to eliminate flat edges in the result patterns by inserting probability to the model. We also preserve the real shape of action potential by using linear curve fitting of one well known electrophysiological model.
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