Zarzoso V, Nandi A K, Bacharakis E
Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK.
IMA J Math Appl Med Biol. 1997 Sep;14(3):207-25.
The separation of the maternal and foetal electrocardiograms (ECGs) from skin electrodes located on the mother's body may be modelled as a blind source separation (BSS) problem. This consists in the reconstruction of a set of unknown mutually independent source signals from the sole knowledge of another set of linear mixtures of the sources, where the mixture pattern is also unknown. Three BSS methods based on cumulants are considered: principal-component analysis (PCA), higher-order singular-value decomposition (HOSVD), and higher-order eigenvalue decomposition (HOEVD). All these methods are applied to the foetal-ECG extraction problem by using real ECG data. The last two methods appear to provide a more satisfactory separation than the first method, with HOEVD offering slightly better results.
从位于母体身体上的皮肤电极分离母体和胎儿心电图（ECG）可被建模为一个盲源分离（BSS）问题。这包括仅根据另一组源信号的线性混合来重建一组未知的相互独立的源信号，其中混合模式也是未知的。考虑了三种基于累积量的BSS方法：主成分分析（PCA）、高阶奇异值分解（HOSVD）和高阶特征值分解（HOEVD）。所有这些方法都通过使用真实的ECG数据应用于胎儿心电图提取问题。后两种方法似乎比第一种方法提供了更令人满意的分离效果，其中HOEVD的结果略好。
