Arrhythmia Detection using Wavelet Transform

K. Daqrouq, I. Abu-Isbeih
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引用次数: 11

Abstract

In this paper, a new method of arrhythmia classification is proposed, this method based on using the continuous wavelet transform (CWT) for analyzing the ECG signal and extracting the desired parameters related to arrhythmia (heart rate variability). Two models are used to simulate the natural signals of heart; these models are used for the assessment of ECG signal processing methods because they have the same characteristics of the natural signals. Another application is the simulation of some cardiac phenomena and abnormalities such as Normocardia, Bradycardia and Tachycardia. The proposed method gives sharp clear threshold between Normocardia, Bradycardia and Tachycardia.
小波变换检测心律失常
本文提出了一种新的心律失常分类方法,该方法基于连续小波变换(CWT)对心电信号进行分析,提取与心律失常(心率变异性)相关的所需参数。采用两种模型模拟心脏的自然信号;这些模型具有与自然信号相同的特征,可用于评价心电信号的处理方法。另一个应用是模拟一些心脏现象和异常,如心律失常、心动过缓和心动过速。该方法给出了正常心动过缓和心动过速的清晰阈值。
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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