Systematic review of computational techniques, dataset utilization, and feature extraction in electrocardiographic imaging

D Mayorca-Torres, AJ León-Salas… - Medical & Biological …, 2025 - Springer
This study aimed to analyze computational techniques in ECG imaging (ECGI)
reconstruction, focusing on dataset identification, problem-solving, and feature extraction …

Differential beat accuracy for ECG family classification using machine learning

A Vadillo-Valderrama, R Goya-Esteban… - IEEE …, 2022 - ieeexplore.ieee.org
Holter systems record the electrocardiogram (ECG), which is used to identify beat families
according to their origin and severity. Many systems have been proposed using signal …

[HTML][HTML] Interpretable manifold learning for T-wave alternans assessment with electrocardiographic imaging

E Sánchez-Carballo, FM Melgarejo-Meseguer… - … Applications of Artificial …, 2025 - Elsevier
T-wave alternans (TWA) is a biomarker for sudden cardiac death prediction, characterized
by subtle variations in the amplitude or morphology of consecutive T-waves in …

Reference for Electrocardiographic Imaging-Based T-Wave Alternans Estimation

E Sánchez-Carballo, FM Melgarejo-Meseguer… - IEEE …, 2024 - ieeexplore.ieee.org
Sudden cardiac death causes multiple deaths annually, and T-wave alternans are a reliable
predictor of this fatal event. Detecting alternans is crucial for reducing disease incidence …

Spatial-temporal signals and clinical indices in electrocardiographic imaging (I): preprocessing and bipolar potentials

R Caulier-Cisterna, M Sanromán-Junquera… - Sensors, 2020 - mdpi.com
During the last years, Electrocardiographic Imaging (ECGI) has emerged as a powerful and
promising clinical tool to support cardiologists. Starting from a plurality of potential …