ECG-BASED HEART BEAT DETECTION USING RATIONAL FUNCTIONS

ECG-BASED HEART BEAT DETECTION USING RATIONAL FUNCTIONS
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使用有理函数进行基于心电图的心跳检测

DOI：
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发表时间：
2016
期刊：
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通讯作者：
Zoltán Gilián
Zoltán Gilián
中科院分区：
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文献类型：
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作者：
Zoltán Gilián

文献摘要

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本文的目的是提出一种新的心跳检测算法，使用合理的ECG信号建模。该算法考虑几个候选心跳位置。对于一个给定的候选人的合理的模型拟合的ECG信号的数值优化和傅立叶部分总和的Malmquist-Takenaka系统。所得到的模型参数被用作分类的基础。分类由SVM分类器执行，SVM分类器在PhysioNet数据库的注释ECG记录上进行训练。
The aim of this paper is to present a novel heart beat detection algorithm using rational modelling of ECG signals. The algorithm considers several candidate beat locations. For a given candidate a rational model is fitted to the ECG signal by means of numerical optimization and Fourier partial sums with respect to the Malmquist-Takenaka system. The resultant model parameters are used as a basis of classification. The classification is performed by an SVM classifier, which is trained on annotated ECG records of the PhysioNet database.