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

Tópicos

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Resumo

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.

Resumo Limpo

wavelet packet transform decompos signal set orthonorm base node provid opportun select appropri set base featur extract paper multilevel basi select mlbs propos preserv inform base wavelet packet decomposit tree remov less inform base appli three exclus criteria frequenc rang nois frequenc energi threshold mlbs achiev accuraci classifi normal heart sound aortic stenosi mitral regurgit aortic regurgit mlbs promis basi select suggest signal small rang frequenc

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