Involving Action Potential Morphology on a New Cellular Automata Model of Cardiac Action Potential Propagation
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
Cellular Automata, Action Potential Propagation,cardiac tissue, Isotropic Pattern, accurate shape of cardiac actionpotential.
A new Cellular Automata Model of Cardiac Action Potential Propagation based on Summation of Excited Neighbors
The heart tissue is an excitable media. A Cellular
Automata is a type of model that can be used to model cardiac action
potential propagation. One of the advantages of this approach against
the methods based on differential equations is its high speed in large
scale simulations. Recent cellular automata models are not able to
avoid flat edges in the result patterns or have large neighborhoods. In
this paper, we present a new model to eliminate flat edges by
minimum number of neighbors.
Cellular Automata, Action Potential Simulation,Isotropic Pattern.