Why the study?
Does a signal processing method based on Morlet wavelet transform distinguish VT/VF patients from healthy persons using QRS-complex variability?
Does a signal processing method based on Morlet wavelet transform distinguish VT/VF patients from healthy persons using QRS-complex variability?
A novel signal processing method using Morlet wavelet transform can estimate QRS-complex variability and distinguish patients prone to malignant ventricular arrhythmias from healthy individuals.
Hypothesis-generating for wavelet QRS variability in VT/VF risk stratification; prospective validation needed before clinical adoption.
The variability of electric and magnetic signals from the heart during the depolarization phase is investigated. A signal processing method is developed, which provides estimates for the beat-to-beat variability of the QRS-complex. The method is based on the decomposition of the depolarization signal into bandpass signals by means of the Morlet wavelet transform. The beat variability of the depolarization signal is estimated by normalized variances of the envelope and instantaneous frequency of bandpass signals. Time intervals of the bandpass filtered depolarization signals having a high signal-to-noise ratio are selected applying an analysis based on phase statistics. The method was tested by computer simulation and experimental data taken from electrocardiographic and magnetocardiographic measurements of healthy persons and patients prone to malignant ventricular tachycardia (VT) or ventricular fibrillation (VF). Results suggest that the calculated variance parameters permit the characterization of beat variable depolarization signals and distinguish VT/VF patients from healthy persons.
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Link et al. (2001) studied this question.
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