基于傅立叶变换的心音记录正常与异常PCG自动分类

Anjali Yadav, M. Dutta, C. Travieso-González, J. B. Alonso
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引用次数: 9

摘要

如今,心血管疾病非常普遍,因此需要对人类进行定期诊断。心音图是分析心音的有效诊断工具。它有助于提供关于心脏临床状况的更好的信息。本文提出了一种利用心电心电图数据区分正常心音和异常心音的算法。对这两种信号进行倒频谱分析,提取心音特征。在支持向量机分类器的帮助下,对提取的特征进行训练和测试。该方法对心音PCG信号进行正常和异常分类的准确率达到95%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Classification of Normal and Abnormal PCG Recording Heart Sound Recording Using Fourier Transform
Cardiovascular diseases are very common these days and there arises a need for regular diagnosis of humans. Phonocardiogram is an effective diagnostic tool for analysing the heart sound. It helps in providing better information regarding clinical condition of the heart. This paper proposes an algorithmic method for differentiating a normal heart sound from an abnormal one using the PCG sound data. Cepstrum analysis has been performed on both types of signals and features are extracted from the heart sound. The extracted features are trained and tested with the help of a support vector machine classifier. The proposed method has achieved an accuracy of 95% in correctly classifying a heart sound PCG signal as normal and abnormal.
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