Automatic Classification of Heartbeats Using Wavelet Neural Network

被引：0

作者：

Radhwane Benali

Fethi Bereksi Reguig

Zinedine Hadj Slimane

机构：

[1] Abou Bekr Belkaid University,Biomedical Engineering Laboratory, Department of Electronics, Faculty of Engineering Sciences

来源：

Journal of Medical Systems | 2012年 / 36卷

关键词：

ECG; Feature extraction; QRS; Classification; WNN; Wavelet; Cardiac arrhythmia;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

The electrocardiogram (ECG) signal is widely employed as one of the most important tools in clinical practice in order to assess the cardiac status of patients. The classification of the ECG into different pathologic disease categories is a complex pattern recognition task. In this paper, we propose a method for ECG heartbeat pattern recognition using wavelet neural network (WNN). To achieve this objective, an algorithm for QRS detection is first implemented, then a WNN Classifier is developed. The experimental results obtained by testing the proposed approach on ECG data from the MIT-BIH arrhythmia database demonstrate the efficiency of such an approach when compared with other methods existing in the literature.

引用

页码：883 / 892

页数：9

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