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Visualization of the current-density distribution for MCG with WPW syndrome patients using independent component analysis

机译:独立分量分析显示WPW综合征患者MCG的电流密度分布

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摘要

The purpose of this study is to evaluate the accessory pathway in the Wolff-Parkinson-White (WPW) syndrome. We measured magnetocardiograms (MCGs) for normal subjects and patients with the WPW syndrome using SQUID magnetometer. It is generally difficult to estimate the accessory pathway by visualization of the current-density distribution (VCDD) because the VCDD has a wide range. Independent component analysis (ICA) is a useful method for separating independent signals from overlapping signals. The source estimation of the accessory pathway was done by the VCDD using ICA. The effect of the accessory pathway was extracted by ICA, and the activity of the accessory pathway was accurately estimated. ICA was able to extract the effect of the accessory pathway. It is confirmed that ICA is a useful method to estimate the VCDD of MCG with WPW syndrome patients.
机译:本研究的目的是评估沃尔夫-帕金森-怀特(WPW)综合征的辅助途径。我们使用SQUID磁力计测量了正常受试者和WPW综合征患者的心电图(MCG)。通常很难通过可视化电流密度分布(VCDD)估计辅助路径,因为VCDD具有广泛的范围。独立分量分析(ICA)是从重叠信号中分离独立信号的有用方法。辅助通路的源估计是由VCDD使用ICA完成的。通过ICA提取辅助途径的作用,并准确估计辅助途径的活性。 ICA能够提取辅助途径的作用。可以肯定的是,ICA是评估WPW综合征患者MCG VCDD的有用方法。

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