Blind Source Separation in Persistent Atrial Fibrillation Electrocardiograms Using Block-Term Tensor Decomposition With Löwner Constraints

The estimation of the atrial activity (AA) signal from electrocardiogram (ECG) recordings is an important step in the noninvasive analysis of atrial fibrillation (AF), the most common sustained arrhythmia encountered in clinical practice. This problem admits a blind source separation (BSS) formulati...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics 2022-04, Vol.26 (4), p.1538-1548
Hauptverfasser:	de Oliveira, P. M. R., Goulart, J. H. de M., Fernandes, C. A. R., Zarzoso, V.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Arrhythmia Atrial fibrillation Atrial Fibrillation - diagnosis Bioengineering Blind source separation block term decomposition Cardiac arrhythmia Cardiology and cardiovascular system Computational modeling Computer Science constrained alternating group lasso Constraints Decomposition EKG electrocardiogram Electrocardiography Electrocardiography - methods Estimation Fibrillation Heart Atria Heart beat Human health and pathology Humans Iterative methods Life Sciences Löwner matrices Mathematical analysis Rational functions Separation Signal and Image Processing Signal processing Signal Processing, Computer-Assisted Signal quality Tensors
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