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Classifying Endogenous Rhythms in Pacemaker ECG Signals

机译:分类起搏器ECG信号中的内源节律

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This article presents the problem of classification of endogenous rhythms with electrocardiography signals coming from patients with implanted cardiac pacemaker. Efficiency of detection of QRS complex was examined by algorithms working in time domain. During the investigation attention was paid to proper selection of level decomposition, good choice of detection threshold as well as choice of wavelet transformation. In case of identification of endogenic rhythm attention was paid to architecture of feedforward neural network, selection of teaching file and the accuracy of classification depending on the activation function used.
机译:本文介绍了来自植入心脏起搏器患者的心电图信号分类的内源节律分类问题。通过在时域工作的算法检查QRS复合物的检测效率。 During the investigation attention was paid to proper selection of level decomposition, good choice of detection threshold as well as choice of wavelet transformation.在鉴定内源性节律的情况下,向前馈神经网络的架构支付了架构,根据所使用的激活函数选择教学文件的选择和分类的准确性。

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