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Quantification of t-wave morphological variability using time-warping methods

Abstract:

The aim of this study is to quantify the variation of the T-wave morphology during a 24-hour electrocardiogram (ECG) recording. Two ECG-derived markers are presented to quantify T-wave morphological variability in the temporal, d<inf>w</inf>, and amplitude, d<inf>a</inf> , domains. Two additional markers, d<inf>w</inf>NL and d<inf>a</inf>NL , that only capture the non-linear component of d<inf>w</inf> and d<inf>a</inf> are also proposed. The proposed markers are used to quantify T-wave time and amplitude variations in 500 24-hour ECG recordings from chronic heart failure patients. Additionally, two mean warped T-waves, used in the calculation of those markers, are proposed to compensate for the rate dependence of the T-wave morphology. Statistical analysis is used to evaluate the correlation between d<inf>w</inf>, d<inf>w</inf>NL , d<inf>a</inf> and d<inf>a</inf>NL and the maximum intra-subject RR range, ∆RR. Results show that the mean warped T-wave is able to compensate for the morphological differences due to RR dynamics. Moreover, the metrics d<inf>w</inf> and d<inf>w</inf>NL are correlated with ∆RR, but d<inf>a</inf> and d<inf>a</inf>NL are not. The proposed d<inf>w</inf> and d<inf>w</inf>NL quantify variations in the temporal domain of the T-wave that are correlated with the RR range and, thus, could possibly reflect the variations of dispersion of repolarization due to changes in heart rate.