Heart sounds classification using motif based segmentation

• Type: Article in International Conference Proceedings Book
• Date: 2014

Authors

Oliveira, SC (Author) Other; Gomes, EF (Author) Other; Jorge, AM (Author) FCUP

Conference proceedings International

Title: ACM International Conference Proceeding Series

Pages: 370-371

18th International Database Engineering and Applications Symposium, IDEAS 2014

Porto, 7 July 2014 through 9 July 2014

Indexing

Scopus - 2 Citations

Other information

Authenticus ID: P-009-S3P

DOI: 10.1145/2628194.2628197

Abstract (EN): In 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.

Language: English

Type (Professor's evaluation): Scientific