基于经验模态分解的心电图信号QRS复合体检测

Z. Bouabida, Z. H. Slimane, F. B. Reguig
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引用次数: 2

摘要

在对信号(生理信号)进行采集和预处理之后,往往是对临床重要参数的提取。在心电图信号中,QRS复合体是诊断心律失常最重要的参数之一。本文将经验模态分解(EMD)方法用于QRS复合物的检测。该方法旨在将非线性和非平稳信号自适应地分解为一系列振幅和频率调制的信号,称为本征模态函数(IMF)。我们在包含不同病理的MIT/BIH数据库的几个信号上测试了我们的算法,我们获得了78%到99%的灵敏度。
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Detection of QRS complex in electrocardiogram signal by the empirical mode decomposition
The acquisition and the pretreatment of the signals (physiological signals) are often followed by the extraction of the parameters of clinical importance. In the case of the electrocardiogram signal (ECG), the QRS complex is one of the most significant parameters for the diagnosis of the cardiac arrhythmias. In this paper the method known as the empirical mode decomposition (EMD) is used for detection of QRS complex. This method aims to decompose nonlinear and non stationary signals adaptively in a series of signals modulated in amplitude and frequency called intrinsic mode function (IMF). We tested our algorithm on several signals of the MIT/BIH database comprising different pathologies, we obtained a sensitivity of 78% to 99%.
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