title: Estimation of atrial fibrillatory wave from single-lead atrial fibrillation electrocardiograms using principal component analysis concepts.
abstract: A new method for the assessment of the atrial fibrillatory wave (AFW) from the ECG is presented. This methodology is suitable for signals registered from Holter systems, where the reduced number of leads is insufficient to exploit the spatial information of the ECG. The temporal dependence of the bio-electrical activity were exploited using principal component analysis. The main features of ventricular and atrial activity were extracted, and several basis signals for each subspace were determined. Hence, the estimated (AFW) are reconstructed exclusively from the basis signals that formed the atrial subspace. Its main advantage with respect to adaptive template subtraction techniques was its robustness to variations in the QRST morphology, which thus minimised QRST residua. The proposed approach was first validated using a database of simulated recordings with known atrial activity content. The estimated AFW was compared with the original AFW, obtaining correlation indices of 0.774 +/- 0.106. The suitability of this methodology for real recordings was also proven, though its application to a set of paroxysmal AF ECGs. In all cases, it was possible to detect the main frequency peak, which was between 4.6 Hz and 6.9 Hz for the patients under study.
authors.affiliation: fcastells@eln.upv.es fcastells@eln.upv.es
authors.forename: F
authors.initials: F
authors.lastname: Castells
authors.forename: C
authors.initials: C
authors.lastname: Mora
authors.forename: J J
authors.initials: JJ
authors.lastname: Rieta
authors.forename: D
authors.initials: D
authors.lastname: Moratal-Pérez
authors.forename: J
authors.initials: J
authors.lastname: Millet
mesh_terms: D000465:Algorithms; D001281:Atrial Fibrillation / Q000175:diagnosis*; D015716:Electrocardiography, Ambulatory / Q000295:instrumentation*; D006801:Humans; D025341:Principal Component Analysis; D012815:Signal Processing, Computer-Assisted