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Deriving the 12-lead ECG from an EASI-lead system via support vector regression

机译:通过支持向量回归从EASI导联系统中导出12导联心电图

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The measuring of all 12-lead electrocardiogram (ECG) is often cumbersome and impractical especially on a long term monitoring. In 1988, Gordon Dower has introduced an EASI-lead system, where only 5 electrodes are used. In order to gain all 12-lead ECG back from this EASI-lead system, Dower’s equation was proposed then. Ever since various attempts have been explored to improve the synthesis accuracy, mostly via Linear regression. This paper presents how Support Vector Regression (SVR) is used to find a set of transfer function for deriving the 12-lead ECG from EASI-lead system. The experiments were conducted to compare the results those of SVR against those of Linear regression and those of Dower’s method. The experimental results have shown that the best performance amongst those methods with the minimum of RMSE for all signals with the standard 12-lead ECG was obtained by SVR, followed by Linear regression and Dower’s equation, respectively.
机译:所有12导联心电图(ECG)的测量通常很麻烦且不切实际,尤其是在长期监测中。 1988年,戈登·道尔(Gordon Dower)引入了仅使用5个电极的EASI导联系统。为了从该EASI导联系统中获得所有12导联的ECG,然后提出了Dower方程。自从进行了各种尝试以提高合成精度的尝试以来,主要是通过线性回归。本文介绍了如何使用支持向量回归(SVR)来找到一组传递函数,以从EASI-lead系统中导出12-lead ECG。进行实验以比较SVR,线性回归和Dower方法的结果。实验结果表明,在这些方法中,对于具有标准12导联心电图的所有信号,均采用最小均方误差最小的最佳性能是通过SVR获得的,其次是线性回归和Dower方程。

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