Quantification of T-wave Morphological Variability Using Time-warping Methods
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, \(d_w\) , and amplitude, \(
- PDF / 983,085 Bytes
- 4 Pages / 595.276 x 790.866 pts Page_size
- 57 Downloads / 222 Views
Biomedical Signal Interpretation and Computational Simulation (BSICoS) group, Arag´on Institute of Engineering Research (I3A), IIS Arag´on, University of Zaragoza, Zaragoza, Spain and Biomedical Research Networking Center (CIBER), Zaragoza, Spain. 2 Institute of Cardiovascular Science, University College London, London, UK.
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, dw , and amplitude, da , domains. Two additional markers, dwNL and daNL , that only capture the non-linear component of dw and da are also proposed. The proposed markers are used to quantify Twave 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 dw , dwNL , da and daNL 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 dw and dwNL are correlated with ∆RR, but da and daNL are not. The proposed dw and dwNL 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. Keywords— Electrocardiogram, morphological variability, repolarization, T-wave, time-warping.
I. I NTRODUCTION The T-wave reflects the spatio-temporal dispersion of repolarization of the ventricular myocytes [1]. Thus, if ionic exchanges during ventricular repolarization or propagation of the electrical impulse throughout the ventricles suffer from any abnormalities, this will be reflected on the morphology of the T-wave [2]. Steep slopes of the T-peak-to-end (Tpe) dynamics, considered as a non-invasive marker to some extent related to enhanced spatio-temporal dispersion of repolarization restitution, have been suggested to be linked to the generation of ventricular arrhythmias that could lead to sudden cardiac death, while flat slopes indicate mechanical heart fatigue predisposing to [3]. The hypothesis of this study is that the information contained in the morphology of the T-wave may provide stronger risk prediction markers than those obtained © Springer Nature Singapore Pte Ltd. 2018 H. Eskola et al. (eds.), EMBEC & NBC 2017, IFMBE Proceedings 65, DOI: 10.1007/978-981-10-5122-7_120
when using the Tpe interval only. Overall shifts in the temporal domain, or misalignments between T-waves, might complicate the comparison and corrupt the measurement of Twave morphological variability. Linear and non-linear temporal re-parameterization (warping) techniques have been used to overcome this limitation, align electrocardiogram (ECG) waves and measure amplitude differe
Data Loading...
