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Separation of Lung Sound from PCG Signals Using Wavelet Transform

机译:使用小波变换将肺音与PCG信号分离

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The Auscultation of the heart sound is a most common method to obtain all the useful information to detect various diseases of cardiovascular system. However one of the main problems of PCG (phonocardiogram) signal analysis is interference of different sound. These sounds may be external or internal. The external sound is avoided by using sound proof room or other method etc. but internal sound like lung sound, vessel sound and muscle contraction sound is unavoidable during the recording of PCG signal. Wavelet is a most successful method for denoising the PCG signal. We have implemented a wavelet based denoising method for separation of lung sound from heart sound. In the wavelet transform (WT) based filter it has been shown that the multiresolution representation of the lung sound signal in the WT domain combined with soft-thresholding can separate the input signal (lung sound) from the nonstationary one (heart sound). The study investigates the different parameter of PCG signal before and after the wavelet based filtering. In this paper we separated the PCG signal from lung sound by different wavelets and found the wavelet which gives the appropriate PCG signal.
机译:心音听诊是获得所有有用信息以检测各种心血管系统疾病的最常用方法。然而,PCG(心电图)信号分析的主要问题之一是不同声音的干扰。这些声音可能是外部的,也可能是内部的。通过使用隔音室或其他方法避免外部声音,但是在记录PCG信号期间不可避免地会产生内部声音,例如肺部声音,血管声音和肌肉收缩声音。小波是对PCG信号进行去噪的最成功方法。我们已经实现了一种基于小波的降噪方法,用于分离肺音和心音。在基于小波变换(WT)的滤波器中,已经显示出WT域中的肺部声音信号的多分辨率表示与软阈值相结合可以将输入信号(肺部声音)与非平稳状态(心音)分开。该研究调查了基于小波滤波前后PCG信号的不同参数。在本文中,我们通过不同的小波将PCG信号与肺部声音分离,并找到给出适当PCG信号的小波。

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