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V Zarzoso

Publications and source records attributed to V Zarzoso.

2 recordsLinked to original sources

Noninvasive fetal electrocardiogram extraction: blind separation versus adaptive noise cancellation.

The problem of the fetal electrocardiogram (FECG) extraction from maternal skin electrode measurements can be modeled from the perspective of blind source separation (BSS). Since no comparison between BSS techniques and other signal processing methods has been made, we compare a BSS procedure based on higher-order statistics and Widrow's multireference adaptive noise cancelling approach. As a best-case scenario for this latter method, optimal Wiener-Hopf solutions are considered. Both procedures are applied to real multichannel ECG recordings obtained from a pregnant woman. The experimental outcomes demonstrate the more robust performance of the blind technique and, in turn, verify the validity of the BSS model in this important biomedical application.

Abdomen↗

Maternal and foetal ECG separation using blind source separation methods.

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.

Biomedical Engineering↗