Heart sounds classification with a fuzzy neural network method with structure learning

  • Authors:

  • Lijuan Jia;Dandan Song;Linmi Tao;Yao Lu

  • Affiliations:

  • Lab of High Volume Language Information Processing & Cloud Computing, Beijing Lab of Intelligent Information Technology School of Computer Science, Beijing Institute of Technology, Beijing, Ch ...;Lab of High Volume Language Information Processing & Cloud Computing, Beijing Lab of Intelligent Information Technology School of Computer Science, Beijing Institute of Technology, Beijing, Ch ...;Department of Computer Science and Technology, Tsinghua University, Beijing, China;Lab of High Volume Language Information Processing & Cloud Computing, Beijing Lab of Intelligent Information Technology School of Computer Science, Beijing Institute of Technology, Beijing, Ch ...

  • Venue:
  • ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
  • Year:
  • 2012

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Abstract

Heart sound analysis is a basic method for cardiac evaluation, which contains physiological and pathological information of various parts of the heart and interactions between them. This paper aims to design a system for analyzing heart sounds including automatic analysis and classification. With the features extracted by wavelet decomposition and Normalized Average Shannon Energy, a novel fuzzy neural network method with structure learning is proposed for the heart sound classification. Experiments with real data demonstrated that our approach can correctly classify all the tested heart sounds even for the ones with previous unseen heart diseases.