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A Time-Frequency Approach for Discrimination of Heart Murmurs

Author(s): Sepideh Jabbari | Hassan Ghassemian

Journal: Journal of Signal and Information Processing
ISSN 2159-4465

Volume: 02;
Issue: 03;
Start page: 232;
Date: 2011;
Original page

Keywords: Phonocardiogram (PCG) | Murmur | Matching Pursuit (MP) | Time-Frequency atom | Clustering

In this paper, a novel framework based on a time-frequency (TF) approach is proposed for detection of murmurs from heart sound signal. First, a high-resolution TF algorithm, matching pursuit, was used to decompose each heart beat into a series of TF atoms selected from a redundant dictionary. Next, representative components of murmurs were identified by clustering the selected atoms of all the beats into a finite number of clusters. Then, Wigner-Ville distribution of the representative components was used to generate a set of 8 features which were fed to a classifier. Experiments with a dataset consisting of heart sounds from 35 normal and 35 pathological subjects showed a classification accuracy of 95.71% in distinguishing murmurs from normal heart sounds.
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