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