Multiscale analysis of heart sound for segmentation using multiscale Hilbert envelope

L. Sharma
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引用次数: 13

Abstract

In this paper a heart sound segmentation algorithm in multiresolution domain is proposed. Wavelet decomposition of heart sound signal grossly segments its components into different subbands. If multiscale Hilbert envelope is computed on reconstructed signals at different scales, it provides suitable markers for first and second heart sound boundaries. The selection of wavelet subband for marker generation is based on analysis of heart sound spectra and energy contribution of wavelet subbands. The heart sound boundaries for S1 and S2 are decided by markers derived from second derivative of Hilbert envelope of the reconstructed subband signal. The proposed method is evaluated using heart sound signal available in the web site of the Department of Medicine, Washington University. The performance of the proposed method is found satisfactory.
基于多尺度希尔伯特包络的心音分割多尺度分析
提出了一种多分辨率域心音分割算法。心音信号的小波分解将其分量大致分割成不同的子带。在不同尺度的重构信号上计算多尺度希尔伯特包络,可以为第一、第二心音边界提供合适的标记。在分析心音谱和小波子带能量贡献的基础上,选择小波子带进行标记生成。S1和S2的心音边界由重构子带信号希尔伯特包络的二阶导数得到的标记决定。使用华盛顿大学医学系网站上提供的心音信号对所提出的方法进行了评估。结果表明,该方法的性能令人满意。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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