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New Algorithms for Continuous Analysis of Long Term ECG Recordings Using Symplectic Geometry and Fuzzy Pattern Recognition

机译:使用辛几何和模糊模式识别的长期ECG录制连续分析新算法

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In this paper, we describe how to analyze continuously ECG of any duration, and we describe a group of new and original algorithms which can do this analysis almost online. These algorithms use symplectic geometric calculus as well as an original fuzzy clustering method for localization of various waves and calculation of different parameters. The programs calculate the isoelectric curve of the ECG, then localize all ECG complexes and delineate the P, QRS and T waves within each complex. Then they calculate various parameters such as spatial area of the QRS wave, QRS-T angle etc. Finally, according to predefined criterions, every complex of ECG is classified into one of several predefined classes and an average prototype of every class is calculated and recorded. Spurious parts and outliers in continuous signal or in calculated parameters are automatically detected. The calculation of the isoelectric curve is performed by using an original fuzzy pattern recognition method operating on a detection function.
机译:在本文中,我们介绍了如何分析任何持续时间的持续ECG,我们描述了一组新的和原始算法,可以在网上进行此分析。这些算法使用辛的几何微积分以及原始模糊聚类方法,用于定位各种波和不同参数的计算。程序计算ECG的等电曲线,然后本地化所有ECG复合物并在每个复合物内描绘P,QRS和T波。然后,计算诸如QRS波的空间区域的各种参数,QRS-T角度等。最后,根据预定义的标准,将ECG的每个复合物分为若干预定义的类中的一个,并且计算并记录每个类的平均原型。 。自动检测连续信号或计算参数中的虚假部件和异常值。通过使用在检测功能上操作的原始模糊模式识别方法来执行等电曲线的计算。

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