Having developed sound mathematical techniques that allow precise mapping of cardiac signals in the time-frequency (TF) and time-scale planes, the next important issue is to extract from these representations information that best reflects the electrophysiologic and anatomic derangement unique to patients at risk of arrhythmias and other cardiac diseases. In this study, the authors present a new method that stratifies the magnitude of the TF transforms of abnormal cardiac signals into distinguishing features by comparing the means of the coefficients of the TF transforms of any study population to the corresponding means of a control population using a standard ANOVA technique. This results in a three-dimensional mapping of the high-resolution ECG into time, frequency, and P value components. Significant energy increases are given positive P values and depressed energies are given negative P values: these are ranked according to a color scale. The method was tested on two study populations: postmyocardial infarction patients with documented ventricular tachycardia (MI+VT, n = 23) and without (MI-VT, n = 40) and patients with congenital long QT syndrome (LQTS, n = 19). Two groups of healthy control subjects (n = 31 and n = 40) were used as a reference group matched for sex. The study results were based on the Morlet analyzing wavelets, with frequencies ranging from 40 to 250 Hz in 10 logarithmically progressing scales, and computed millisecond per millisecond over a 350-ms analyzing time window, starting from 100 ms before the onset of the QRS. The patients with MI+VT displayed significantly increased high-frequency components in the 40-250-Hz frequency range, corresponding to prolonged QRS duration and late potentials in the area from 80 to 150 ms after QRS onset. Significantly depressed energy (P < 10(-4)) was also observed for the 40-106-Hz frequency range in the first 50 ms of the QRS complex, mainly in lead Y and in the magnitude vector. In patients with LQTS, significant modifications (P < 10(-2)) were observed in the first half of the QRS and in the ST-segment, in all leads, revealing anomalies in the genesis of the ventricular depolarization and repolarization processes. In conclusion, the authors propose a new method for the stratification of abnormal TF components occurring in the signal-averaged high-resolution electrocardiogram of patients at risk of VT and fibrillation under different pathologic conditions.