A new neural network model based on the LVQ algorithm for multi-class classification of arrhythmias

This paper describes the application of competitive neural networks with the LVQ algorithm for classification of electrocardiogram signals (ECG). For this study we used the MIT–BIH arrhythmia database with 15 classes. Three architectures were developed with a modular approach for classification. Com...

Full description

Saved in:
Bibliographic Details
Published in:Information sciences 2014-09, Vol.279, p.483-497
Main Authors: Melin, Patricia, Amezcua, Jonathan, Valdez, Fevrier, Castillo, Oscar
Format: Article
Language:English
Subjects:
Arrhythmias
Classification
Clustering
LVQ
Neural network
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper describes the application of competitive neural networks with the LVQ algorithm for classification of electrocardiogram signals (ECG). For this study we used the MIT–BIH arrhythmia database with 15 classes. Three architectures were developed with a modular approach for classification. Compared with other methods that have been developed for classification of arrhythmias with this same database, the proposed approach produces very good results, because the entire database was used. Simulation results are presented, and a statistical test was performed to compare the three architectures which were very similar in the classification results.
ISSN:0020-0255
1872-6291
DOI:10.1016/j.ins.2014.04.003