A critical review of heart sound signal segmentation algorithms

Abstract

This paper discusses four heart sound segmentation (HSS) methods: Wavelet transform, Fractal decomposition, Hilbert Transform, and Shannon Energy Envelogram, in order to identify the different cardiac sounds. Many research studies related to heart signal analysis, have adopted these methods to give high heart sound segmentation results, especially, for the identification of first and second heart sounds and murmurs. Performance of the heart sound segmentation results have also been compared with one other to identify the most efficient method(s), and it has been found that Shannon energy envelogram provides the best accuracies among the segmentation methods. Understandings of the segmentation methods for heart sound may pave the way for more advanced studies in other heart-related researches, including heart sound classifications.