Estimating conductivity distribution of transmural wedges of the ventricle using parallel genetic algorithms

In this work we use a computational human left ventricular wedge to simulate regions of abnormal intra- and extra-cellular conductivities that mimic some known pathological conditions. We propose a method based on genetic algorithms that aims on estimating the distribution of intra- and extra-cellul...

Full description

Saved in:
Bibliographic Details
Main Authors: Martins, D.M.S., Xavier, C.R., Santos, E.P., Vieira, V.F., Oliveira, R.S., Weber dos Santos, R.
Format: Conference Proceeding
Language:English
Subjects:
Cardiac tissue
Cardiology
Computational modeling
Conductivity
Distributed computing
Electrocardiography
Extracellular
Genetic algorithms
Humans
Pathology
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this work we use a computational human left ventricular wedge to simulate regions of abnormal intra- and extra-cellular conductivities that mimic some known pathological conditions. We propose a method based on genetic algorithms that aims on estimating the distribution of intra- and extra-cellular conductivities, by comparing cardiac simulations to some given transmural electrograms. The methods were developed for distributed systems and the results were obtained in a cluster composed of 8 computers interconnected by a fast network switching device. The results suggest that the proposed method is able to approximately estimate both intra- and extra-cellular conductivity distributions from transmural electrograms with an accuracy of 40%.
ISSN:0276-6574
2325-8853