Variability of Ventricular Repolarization Dispersion Quantified by Time-Warping the Morphology of the T-Waves

• Published in: IEEE transactions on biomedical engineering Vol. 64; no. 7; pp. 1619 - 1630
• Main Authors: Ramirez, Julia, Orini, Michele, Tucker, J. Derek, Pueyo, Esther, Laguna, Pablo
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Amplitudes; Biomedical measurement; Computer Simulation; Dispersion; Domains; EKG; Electrocardiogram; Electrocardiography; Electrocardiography - methods; Genetic variability; Heart Conduction System - physiology; Heart rate; Humans; Markers; Models, Cardiovascular; morphological variability; Morphology; Noise levels; Pattern Recognition, Automated - methods; repolarization; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Solids; Spatial distribution; T-wave; Temporal distribution; Time-domain analysis; time-warping; Ventricle; Ventricular Function - physiology
• ISSN: 0018-9294; 1558-2531; 1558-2531
• DOI: 10.1109/TBME.2016.2614899

Objective: We propose two electrocardiogram (ECG)-derived markers of T-wave morphological variability in the temporal, d ω , and amplitude, d α , domains. Two additional markers, d ω NL and d α NL , restricted to measure the nonlinear information present within d ω and d α are also proposed. Methods: We evaluated the accuracy of the proposed markers in capturing T-wave time and amplitude variations in 3 situations: 1) In a simulated set up with presence of additive Laplacian noise, 2) when modifying the spatio-temporal distribution of electrical repolarization with an electro-physiological cardiac model, and 3) in ECG records from healthy subjects undergoing a tilt table test. Results:The metrics d ω , d α , d ω NL , and d α NL followed T-wave time- and amplitude-induced variations under different levels of noise, were strongly associated with changes in the spatio-temporal dispersion of repolarization, and showed to provide additional information to differences in the heart rate, QT and T pe intervals, and in the T-wave width and amplitude. Conclusion: The proposed ECG-derived markers robustly quantify T-wave morphological variability, being strongly associated with changes in the dispersion of repolarization. Significance: The proposed ECG-derived markers can help to quantify the variability in the dispersion of ventricular repolarization, showing a great potential to be used as arrhythmic risk predictors in clinical situations.