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dc.contributor.authorElsa Ferreira Gomesen
dc.contributor.authorAlípio Jorgeen
dc.description.abstractIn this paper we describe an algorithm for heart sound classification (classes Normal, Murmur and Extrasystole) based on the discretization of sound signals using the SAX (Symbolic Aggregate Approximation) representation. The general strategy is to automatically discover relevant top frequent motifs and relate them with the occurrence of systolic (S1) and diastolic (S2) sounds in the audio signals. The algorithm was tuned using motifs generated from a collection of audio signals obtained from a clinical trial in a hospital. Validation was performed on a separate set of unlabeled audio signals. Results indicate ability to improve the precision of the classification of the classes Normal and Murmur.Copyright 2014 ACM Heart sound classification motif discovery time series analysis SAX.en
dc.titleHeart sounds classification using motif based segmentationen
Appears in Collections:LIAAD - Indexed Articles in Conferences

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