NONLINEAR PHENOMENA IN COMPLEX SYSTEMS
An Interdisciplinary Journal

2009, Vol.12, No.1, pp.92-96


Prediction of Paroxysmal Atrial Fibrillation Onset through Wavelet-Analysis of the Heart Rate Variability.
M. V. Voitikova and A. P. Voitovich

A new algorithm for completely automated wavelet transform analysis of RR-intervals featuring paroxysmal atrial fibrillation (PAF) has been developed. The power spectrum of wavelet-coefficients of RR-intervals sequence was intended to predict the onset of PAF. The absence of a long scale correlation of the wavelet-coefficients indicates on independence of RR-intervals and chaotic character of atrium excitation for the patients prone to atrial fibrillation. On the contrary, there is correlation of all RR-intervals for healthy patients. The PAF predictor uses the diagnostic criterion: 5-10 time increase of the amplitude of wavelet-coefficients precedes the onset of paroxysm. The detection efficiency was validated on ECG database of 25 patients with documented AF and a control group of 20 people.
Key words: wavelet transform, electrocardiogram, atrial fibrillation, arrhythmia

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