基于PCG信号分析的智能算法在心脏病诊断中的应用

Mohammed Nabih-Ali, E. El-Dahshan, Ashraf S Yahia
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引用次数: 28

摘要

提出了一种基于心音图(PCG)的心脏病智能诊断算法。该技术包括四个阶段:数据采集、预处理、特征提取和分类。本研究采用PASCAL心音数据库。第二阶段涉及去除PCG信号中的噪声和伪影。特征提取阶段采用离散小波变换(DWT)进行。最后,将人工神经网络(ANN)用于分类阶段,总体准确率达到97%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Heart Diseases Diagnosis Using Intelligent Algorithm Based on PCG Signal Analysis
This paper presents an intelligent algorithm for heart diseases diagnosis using phonocardiogram (PCG). The proposed technique consists of four stages: Data acquisition, pre-processing, feature extraction and classification. PASCAL heart sound database is used in this research. The second stage concerns with removing noise and artifacts from the PCG signals. Feature extraction stage is carried out using discrete wavelet transform (DWT). Finally, artificial neural network (ANN) has been used for classification stage with an overall accuracy 97%.
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