A compact matrix model for atrial electrograms for tissue conductivity estimation

Finding the hidden parameters of the cardiac electrophysiological model would help to gain more insight on the mechanisms underlying atrial fibrillation, and subsequently, facilitate the diagnosis and treatment of the disease in later stages. In this work, we aim to estimate tissue conductivity from recorded electrograms as an indication of...

Modelling and Analysis of Atrial Epicardial Electrograms: An approach based on graph signal processing and confirmatory factor analysis

Atrial fibrillation (AF) is a frequently encountered cardiac arrhythmia characterized by rapid and irregular atrial activity, which increases the risk of strokes, heart failure and other heart-related complications. The mechanisms of AF are complicated. Although various mechanisms were proposed in previous research, the precise mechanisms of AF...

Characterization of unipolar electrogram morphology: A novel tool for quantifying conduction inhomogeneity

Aims: Areas of conduction inhomogeneity (CI) during sinus rhythm may facilitate the initiation and perpetuation of atrial fibrillation (AF). Currently, no tool is available to quantify the severity of CI. Our aim is to develop and validate a novel tool using unipolar electrograms (EGMs) only to quantify the severity of CI in the atria....

Atrial extrasystoles enhance low-voltage fractionation electrograms in patients with atrial fibrillation

BACKGROUND AND AIMS: Atrial extrasystoles (AES) provoke conduction disorders and may trigger episodes of atrial fibrillation (AF). However, the direction- and rate-dependency of electrophysiological tissue properties on epicardial unipolar electrogram (EGM) morphology is unknown. Therefore, this study examined the impact of spontaneous AES on...