Algorithm for Feature Extraction of Heart Sound Signal Based on Sym7 Wavelet

Abstract:

In order to extract pathological features of heart sound signal accurately, an algorithm for extracting the sub-band energy is developed based on the wavelet packet analysis. Through the spectrum analysis of heart sound signal, the sym7 wavelet, with high energy concentration and good time localization, is taken as the mother function, and the best wavelet packet basis of heart sound signal is picked out. Then, various heart sound signals are decomposed into four levels and the wavelet packet coefficients of the best basis are obtained. According to the equal-value relation between wavelet packet coefficients and signal energy in time domain, the normalized sub-band energy of the best basis is extracted as the feature vector. The mean of class separability measure is 3.049, which indicates that the algorithm is effective for feature extraction of heart sound signal.

• Periodical: Advanced Engineering Forum (Volume 1)
• Pages: 252-256
• DOI: https://doi.org/10.4028/www.scientific.net/AEF.1.252
• Online since: September 2011
• Authors: Guo Hua Zhang, Zhong Fan Yuan, Shi Xuan Liu
• Keywords: Class Separability Measure, Feature Extraction, Heart Sound Signal, Wavelet Packet Algorithm

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