{'fraction_non_alphanumeric': 0.03064699205448354, 'fraction_numerical': 0.0, 'mean_word_length': 5.345323741007194, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
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.