Multi-level basis selection of wavelet packet decomposition tree for heart sound classification.

Citation

Safara, Fatemeh and C. Doraisamy, Shyamala and Azman, Azreen and Jantan, Azrul and Abdullah Ramaiah, Asri Ranga (2013) Multi-level basis selection of wavelet packet decomposition tree for heart sound classification. Computers in Biology and Medicine, 43 (10). pp. 1407-1414. ISSN 0010-4825; ESSN: 1879-0534

Abstract

Wavelet packet transform decomposes a signal into a set of orthonormal bases (nodes) and provides opportunities to select an appropriate set of these bases for feature extraction. In this paper, multi-level basis selection (MLBS) is proposed to preserve the most informative bases of a wavelet packet decomposition tree through removing less informative bases by applying three exclusion criteria:frequency range, noise frequency, and energy threshold. MLBS achieved an accuracy of 97.56% for classifying normal heart sound, aortic stenosis, mitral regurgitation, and aortic regurgitation. MLBS is a promising basis selection to be suggested for signals with a small range of frequencies.

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Additional Metadata

Item Type:	Article
Divisions:	Faculty of Computer Science and Information Technology
DOI Number:	https://doi.org/10.1016/j.compbiomed.2013.06.016
Publisher:	Elsevier
Keywords:	Phonocardiographic signal (PCG); Heart murmur; Wavelet packet transform; Multi-level basis selection; Feature extraction; Relative energy; Support vector machine.
Depositing User:	Ms. Nida Hidayati Ghazali
Date Deposited:	03 Jun 2014 03:44
Last Modified:	28 Jan 2016 04:54
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1016/j.compbiomed.2013.06.016
URI:	http://psasir.upm.edu.my/id/eprint/30560
Statistic Details:	View Download Statistic

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