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Electrocardiogram characterization using wavelet analysis

机译:小波分析的心电图表征

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The electrocardiograph (ECG) is a graphical representation of the forces generated during cardiac activity, and is an essential tool for the diagnosis of cardiac abnormalities. An automatic ECG analyzer will provide a cardiologist with a tool allowing faster and more accurate diagnosis. The analysis consists of the measurement of the amplitudes, durations and morphologies of the P, QRS and T waves. This paper deals with the measure of QRS duration, R spikes detection (arrhythmia), and the starting and vanishing time of the T wave. A comparison of different methods based on the derivatives and filtering for the extraction of ECG characteristics is presented. We show that wavelet analysis gives better results than classical methods, and enables a finer characterization of the parameters.
机译:心电图仪(ECG)是心脏活动过程中产生的力的图形表示,并且是诊断心脏异常的必不可少的工具。自动的ECG分析仪将为心脏病专家提供一种工具,可以更快,更准确地进行诊断。分析包括对P波,QRS波和T波的幅度,持续时间和形态的测量。本文讨论QRS持续时间,R峰值检测(心律不齐)以及T波的开始和消失时间的量度。比较了基于导数和滤波的不同方法提取心电图特征的方法。我们表明,小波分析比传统方法提供了更好的结果,并且可以对参数进行更好的表征。

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