Detection of heart sounds S1 and S2 using optimized S-transform and back — Propagation Algorithm

Vishal Kumar Shivhare, S. N. Sharma, D. K. Shakya
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引用次数: 6

Abstract

This paper describes a method for the detection of heart sounds S1 and S2 using Back-Propagation Algorithm (BPA). The proposed method works satisfactorily on the heart sounds with murmur or noisy data. The work can be divided into four main parts: (i) localization by optimized S-transform, (ii) boundary detection of heart sounds S1 and S2 based on Shannon energy of S-transform, (iii) feature extraction using Singular Value Decomposition (SVD), and (iv) classification using ANN tool known as BPA. In this paper, we have compared the performance parameters like sensitivity and specificity of BPA results with other existing methods and improvement is observed in their values.
利用优化的s变换和反向传播算法检测心音S1和S2
本文介绍了一种利用反向传播算法(BPA)检测心音S1和S2的方法。该方法对有杂音或噪声的心音检测效果满意。该工作可分为四个主要部分:(i)通过优化的s变换进行定位,(ii)基于s变换的Shannon能量对S1和S2心音进行边界检测,(iii)使用奇异值分解(SVD)进行特征提取,(iv)使用人工神经网络(BPA)工具进行分类。在本文中,我们将BPA结果的灵敏度、特异性等性能参数与其他现有方法进行了比较,发现其数值有所提高。
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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