Classifying heart sounds using multiresolution time series motifs: an exploratory study

  • Authors:
  • Elsa Ferreira Gomes;Alípio M. Jorge;Paulo J. Azevedo

  • Affiliations:
  • ISEP/IPP-School of Engineering, Polytechnic of Porto, Portugal;DCC-FCUP, Universidade do Porto, Portugal;HASLab/INESC TEC

  • Venue:
  • Proceedings of the International C* Conference on Computer Science and Software Engineering
  • Year:
  • 2013

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Abstract

The aim of this work is to describe an exploratory study on the use of a SAX-based Multiresolution Motif Discovery method for Heart Sound Classification. The idea of our work is to discover relevant frequent motifs in the audio signals and use the discovered motifs and their frequency as characterizing attributes. We also describe different configurations of motif discovery for defining attributes and compare the use of a decision tree based algorithm with random forests on this kind of data. Experiments were performed with a dataset obtained from a clinic trial in hospitals using the digital stethoscope DigiScope. This exploratory study suggests that motifs contain valuable information that can be further exploited for Heart Sound Classification.