title: Alteration of the P-wave non-linear dynamics near the onset of paroxysmal atrial fibrillation.
abstract: The analysis of P-wave variability from the electrocardiogram (ECG) has been suggested as an early predictor of the onset of paroxysmal atrial fibrillation (PAF). Hence, a preventive treatment could be used to avoid the loss of normal sinus rhythm, thus minimising health risks and improving the patient's quality of life. In these previous studies the variability of different temporal and morphological P-wave features has been only analysed in a linear fashion. However, the electrophysiological alteration occurring in the atria before the onset of PAF has to be considered as an inherently complex, chaotic and non-stationary process. This work analyses the presence of non-linear dynamics in the P-wave progression before the onset of PAF through the application of the central tendency measure (CTM), which is a non-linear metric summarising the degree of variability in a time series. Two hour-length ECG intervals just before the arrhythmia onset belonging to 46 different PAF patients were analysed. In agreement with the invasively observed inhomogeneous atrial conduction preceding the onset of PAF, CTM for all the considered P-wave features showed higher variability when the arrhythmia was closer to its onset. A diagnostic accuracy around 80% to discern between ECG segments far from PAF and close to PAF was obtained with the CTM of the metrics considered. This result was similar to previous P-wave variability methods based on linear approaches. However, the combination of linear and non-linear methods with a decision tree improved considerably their discriminant ability up to 90%, thus suggesting that both dynamics could coexist at the same time in the fragmented depolarisation of the atria preceding the arrhythmia.
authors.affiliation: Research Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, Spain.
authors.forename: Arturo
authors.initials: A
authors.lastname: Martínez
authors.affiliation: Centre for Biomedical Engineering, Department of Mechanical Engineering Sciences, University of Surrey, UK.
authors.forename: Daniel
authors.initials: D
authors.lastname: Abásolo
authors.affiliation: Research Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, Spain. Electronic address: raul.alcaraz@uclm.es.
authors.forename: Raúl
authors.initials: R
authors.lastname: Alcaraz
authors.affiliation: Biomedical Synergy, Electronic Engineering Department, Universidad Politécnica de Valencia, Spain.
authors.forename: José J
authors.initials: JJ
authors.lastname: Rieta
mesh_terms: D001281:Atrial Fibrillation / Q000175:diagnosis* / Q000503:physiopathology*; D015331:Cohort Studies; D003663:Decision Trees; D004562:Electrocardiography / Q000379:methods*; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D017711:Nonlinear Dynamics; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors
keywords: Atrial fibrillation; Central tendency measure; Electrocardiogram; Non-linear; P-wave