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Classification of bundle branch blocks using multilayered perceptron network

Proceeding of The International Conference on Control System, Computing and Engineering (ICCSCE 2011) at Penang, Malaysia on 25 November 2011 through 27 November 2011. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp

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Bibliographic Details
Main Authors: Megat Syahirul Amin, Megat Ali, Aisyah Hartini, Jahidin, Ahmad Nasrul, Norali, Mohd Hanafi, Mat Som
Other Authors: megatsyahirul@salam.uitm.edu.my
Format: Working Paper
Language:English
Published: IEEE Conference Publications 2014
Subjects:
Bundle branch blocks
Multilayered perceptron network
Performance metrics
Training algorithms
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/35375
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spelling my.unimap-353752014-06-11T08:29:35Z Classification of bundle branch blocks using multilayered perceptron network Megat Syahirul Amin, Megat Ali Aisyah Hartini, Jahidin Ahmad Nasrul, Norali Mohd Hanafi, Mat Som megatsyahirul@salam.uitm.edu.my ahmadnasrul@unimap.edu.my Bundle branch blocks Multilayered perceptron network Performance metrics Training algorithms Proceeding of The International Conference on Control System, Computing and Engineering (ICCSCE 2011) at Penang, Malaysia on 25 November 2011 through 27 November 2011. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp Development of automated and accurate techniques for ECG recognition is important for diagnosis of heart diseases. Arrhythmic signals occur due to the disturbances to the rate, regularity, nodes and conduction path of the electrical impulses. Bundle branch block arises from defects of the conduction pathways involving blockage of electrical impulses through the bundle branches. This paper investigates MLP network for classification of bundle branch block arrhythmias. Trainings were conducted for varying network topologies with different training algorithms. A 98.2% overall detection accuracy was achieved over 90 beat samples. Results show that the Levenberg-Marquardt algorithm managed to achieve 100% recognition accuracy for all network topologies. 2014-06-11T08:29:35Z 2014-06-11T08:29:35Z 2011 Working Paper p. 531-535 978-145771642-3 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6190583&tag=1 http://dspace.unimap.edu.my:80/dspace/handle/123456789/35375 10.1109/ICCSCE.2011.6190583 en Proceeding of The International Conference on Control System, Computing and Engineering (ICCSCE 2011); IEEE Conference Publications
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Bundle branch blocks
Multilayered perceptron network
Performance metrics
Training algorithms
spellingShingle Bundle branch blocks
Multilayered perceptron network
Performance metrics
Training algorithms
Megat Syahirul Amin, Megat Ali
Aisyah Hartini, Jahidin
Ahmad Nasrul, Norali
Mohd Hanafi, Mat Som
Classification of bundle branch blocks using multilayered perceptron network
description Proceeding of The International Conference on Control System, Computing and Engineering (ICCSCE 2011) at Penang, Malaysia on 25 November 2011 through 27 November 2011. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp
author2 megatsyahirul@salam.uitm.edu.my
author_facet megatsyahirul@salam.uitm.edu.my
Megat Syahirul Amin, Megat Ali
Aisyah Hartini, Jahidin
Ahmad Nasrul, Norali
Mohd Hanafi, Mat Som
format Working Paper
author Megat Syahirul Amin, Megat Ali
Aisyah Hartini, Jahidin
Ahmad Nasrul, Norali
Mohd Hanafi, Mat Som
author_sort Megat Syahirul Amin, Megat Ali
title Classification of bundle branch blocks using multilayered perceptron network
title_short Classification of bundle branch blocks using multilayered perceptron network
title_full Classification of bundle branch blocks using multilayered perceptron network
title_fullStr Classification of bundle branch blocks using multilayered perceptron network
title_full_unstemmed Classification of bundle branch blocks using multilayered perceptron network
title_sort classification of bundle branch blocks using multilayered perceptron network
publisher IEEE Conference Publications
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/35375
_version_ 1643797777845583872
score 13.214268

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