ECG-based estimation of respiration-induced autonomic modulation of AV nodal conduction during atrial fibrillation.

ABSTRACT: Introduction: Information about autonomic nervous system (ANS) activity may offer insights about atrial fibrillation (AF) progression and support personalized AF treatment but is not easily accessible from the ECG. In this study, we propose a new approach for ECG-based assessment of respiratory modulation in atrioventricular (AV) nodal refractory period and conduction delay. Methods: A 1-dimensional convolutional neural network (1D-CNN) was trained to estimate respiratory modulation of AV nodal conduction properties from 1-minute segments of RR series, respiration signals, and atrial fibrillatory rates (AFR) using synthetic data that replicates clinical ECG-derived data. The synthetic data were generated using a network model of the AV node and 4 million unique model paramete

SUBMITTER: Plappert F 

PROVIDER: S-EPMC11110927 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature