基于离散小波变换(DWT)的心音信号分割

S. Debbal
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引用次数: 0

摘要

在一个心动周期中出现异常音,为各种疾病提供了有价值的信息。早期发现各种疾病是必要的;它是通过一种简单的技术来完成的:心音图。心音描记术,以记录不同频率的振动或振荡为基础,可听或不可听,这些振动或振荡对应于正常和异常的心音它为临床医生提供了一种辅助工具来记录听诊时听到的心音。心内语音心动图的进步,结合信号处理技术,强烈地重新燃起了研究人员对心音和杂音的兴趣。本文提出了一种基于小波变换(DWT)和PCG信号香农能量去噪的心音(第一声和第二声,S1和S2)和心音检测算法。该算法可以分离单个声音(S1或S2)和杂音,从而对其平均持续时间进行评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Heart cardiac’s sounds signals segmentation by using the discrete wavelet transform (DWT)
The presence of abnormal sounds in one cardiac cycle, provide valuable information on various diseases.Early detection of various diseases is necessary; it is done by a simple technique known as: phonocardiography. The phonocardiography, based on registration of vibrations or oscillations of different frequencies, audible or not, that correspond to normal and abnormal heart sounds. It provides the clinician with a complementary tool to record the heart sounds heard during auscultation. The advancement of intracardiac phonocardiography, combined with signal processing techniques, has strongly renewed researchers’ interest in studying heart sounds and murmurs. This paper presents an algorithm based on the denoising by wavelet transform (DWT) and the Shannon energy of the PCG signal, for the detection of heart sounds (the first and second sounds, S1 and S2) and heart murmurs. This algorithm makes it possible to isolate individual sounds (S1 or S2) and murmurs to give an assessment of their average duration.
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