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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/21291

Title: ECG classification using wavelet transform and Discriminant Analysis
Authors: Farah Nur Atiqah, Francis Abdullah
Fazly, Salleh
Rosli, Besar
E-mail: marianne_julie@yahoo.co.uk
fazly.salleh.abas@mmu.edu.my
rosli@mmu.edu.my
Keywords: Cardiac conditions
Wavelet
Discriminant analysis
Distance metric
Issue Date: 27-Feb-2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: p. 191-196
Series/Report no.: Proceedings of the International Conference on Biomedical Engineering (ICoBE 2012)
Abstract: This paper focuses on two cardiac conditions, the supraventricular ectopy and the ventricular ectopy. Four different mother wavelets are used to produce sets of features. Results shows that each cardiac conditions beat has its own unique characteristics and also decomposition of different mother wavelet produced different degree in discriminative power. The Discriminant Analysis Classifier of different distance metric (linear, quadratic and mahalanobis) are tested. Classification performance mostly reached more than 90% for both individual feature and combined feature classification.
Description: Link to publisher's homepage at http://ieeexplore.ieee.org/
URI: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6179003
http://hdl.handle.net/123456789/21291
ISBN: 978-145771989-9
Appears in Collections:Conference Papers

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