A multi-spot exploration of the topological structures of the reconstructed phase-space for the detection of cardiac murmurs.
Annu Int Conf IEEE Eng Med Biol Soc
; 2015: 4194-7, 2015.
Article
em En
| MEDLINE
| ID: mdl-26737219
ABSTRACT
Acoustic heart signals are generated by a turbulence effect created when the heart valves snap shut, and therefore carrying significant information of the underlying functionality of the cardiovascular system. In this paper, we present a method for heart murmur classification divided into three major steps:
a) features are extracted from the heart sound; b) features are selected using a Backward Feature Selection algorithm; c) signals are classified using a K-nearest neighbor's classifier. A new set of fractal features are proposed, which are based on the distinct signatures of complexity and self-similarity registered on the normal and pathogenic cases. The experimental results show that fractal features are the most capable of describing the non-linear structure and the underlying dynamics of heart sounds among the all feature families tested. The classification results achieved for the mitral auscultation spot (88% of accuracy) are in agreement with the current state of the art methods for heart murmur classification.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Processamento de Sinais Assistido por Computador
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Sopros Cardíacos
Tipo de estudo:
Diagnostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2015
Tipo de documento:
Article