Classification of Branch Block Beats using Higher Order Spectral Analysis and Neural Networks

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This paper appears in:
Signal Processing and Communications Applications, 2006 IEEE 14th
Date of Conference: 17-19 April 2006
Author(s): Torun, M.U.
Elektrik ve Elektron. Muhendisligi Bolumu, Dokuz Eylul Univ., Izmir
Isler, Y. ; Kuntalp, D. ; Kuntalp, M.
Page(s): 1 - 4
Product Type: Conference Publications

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Abstract

In this study, it is aimed to classify branch block beats. A total number of 6170 beats related to 3 types of classes are extracted from MIT/BIH arrhythmia database and their bispectrums are calculated using TOR method. The area defined by the frequency values where the value of the energy of bispectrum is 95% of the maximum value in both axes is calculated. This area information is used as a one dimensional feature vector to feed the neural network designed as a classifier. The overall performance of the system is calculated as 94.2%. This study shows that higher order spectral analysis is a promising tool for arrhythmia beat classification

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Additional Details
References (10)

On page(s): 1
Conference Location : Antalya
Print ISBN: 1-4244-0238-7
INSPEC Accession Number: 9095741
Digital Object Identifier : 10.1109/SIU.2006.1659736
Date of Current Version : 31 July 2006
Issue Date : 17-19 April 2006

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