2008, Vol.11, No.3, pp.373-378

An algorithm for completely automated wavelet transform (WT) analysis of ECG signals featuring atrial fibrillation (AF), one of the most common arrhythmia, has been developed. WT based algorithm was intended to differentiate ECG signals with non-terminating permanent AF and signals with paroxysmal AF (spontaneous self-terminated AF). Discrete WT of ECG has been used for identification of QRS-complexes on the basis of threshold criterion for corresponding wavelet coefficients for the purpose to remove the ventricular signal parts. Then, with continuous WT we have decomposed the remainder ECG signal (the atrial activity) into different scales (frequency bands). The distribution of wavelet power spectrum is a discriminant diagnostic criterion of AF forms - a permanent or paroxysmal AF. If the WT power spectrum has a local maximum at scale higher than some predefine threshold parameter, AF is likely terminated within up to several minutes, i.e. we can define paroxysmal AF. For ECG with WT power spectrum the local maximum at scale lower than threshold parameter, AF is likely permanent AF.
Key words: wavelet transform, electrocardiogram, atrial fibrillation, arrhythmia

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