Beat-to-beat wavelet variance of the QRS complex as a marker of arrhythmogenic substrate in ventricular tachycardia patients

This study proposes a wavelet transform based technique to assess the beat-to-beat variation of the QRS signal in post-myocardial infarction patients with sustained monomorphic ventricular tachycardia. Recent electrophysiological investigations suggested that the diminished synchrony between the normal myocardium and the scarred arrhythmogenic tissue bordering a myocardial infarction area gives rise to beat-variable ECG signal components. Using a mathematical model of small variations in a largely repetitive waveform, we show that the inherent alignment errors (trigger jitter) of the high-resolution ECG (HRECG) can artificially increase the value of the time-domain beat-to-beat variance, making it less valuable as a marker of beat-variable signal components. To overcome this drawback, we propose the wavelet based approach which discriminates between the different factors responsible for the beat variability (the alignment error and the beat-variable signal components). The Morlet wavelet transform is performed on HRECG signals from normal individuals (control group) and post-myocardial infarction patients with documented ventricular tachycardia. Electrical variability is quantitatively assessed via the beat-to-beat wavelet variance measurements. A marker of arrhythmogenic induced variance which achieves a good performance in discrimination of ventricular tachycardia patients from normal subjects was found between 200 Hz and 300 Hz. This finding is in agreement with the proposed mathematical model which states that the useful part of the time-frequency map is shifted upward in a precise mathematical way, as the variance induced by the beat-variable arrhythmogenic signals depend on the frequency characteristics of the first derivative of these signals. We conclude that the dynamics of the arrhythmogenic substrate as revealed by the beat-to-beat wavelet variance can be a new estimator of ventricular tachycardia risk. Keywords: beat-to-beat variance, wavelet transform, ventricular tachycardia