MULTIRESOLUTION DECOMPOSITION OF THE SIGNAL-AVERAGED ECG USING THE MALLAT APPROACH FOR PREDICTION OF ARRHYTHMIC EVENTS AFTER MYOCARDIAL-INFARCTION

The aim of this study was to analyze the ability of the multiresolutio n decomposition of the signal-averaged electrocardiogram (EGG) to disc riminate between patients who develop life-threatening ventricular arr hythmias after myocardial infarction and those who do not and to compa re the predictive values of this approach with those obtained from the analysis of ventricular late potentials in the time domain. Signal-av eraged ECGs of 769 prospectively included patients were analyzed. A to tal of 42 arrhythmic events occurred during the follow-up period. For numerical calculations of wavelet analysis, the total and relative ene rgies of the QRS complex were obtained in seven frequency bands. The c ombination of the relative energy in the frequency bands 7.8-15.6 Hz a nd 62.5-125 Hz enhanced statistical performance as compared with the t ime-domain parameters (positive predictive accuracy, 11.3 vs 8.2%). Co mbining wavelet transform and time-domain parameters enhanced the pred ictive values even more (positive predictive accuracy, 14.3%) compared with applying each method alone.