ArticleFrontiers in physiology2021
Non-invasive Characterization of Human AV-Nodal Conduction Delay and Refractory Period During Atrial Fibrillation.
Article in Frontiers in physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- ECG-based beat-to-beat assessment of AV node conduction properties during AF.Frontiers in physiology · 2025Article
- ECG-based estimation of respiration-induced autonomic modulation of AV nodal conduction during atrial fibrillation.Frontiers in physiology · 2024Article
- Model-based estimation of AV-nodal refractory period and conduction delay trends from ECG.Frontiers in physiology · 2023Article
- An atrioventricular node model incorporating autonomic tone.Frontiers in physiology · 2022Article
- ECG based assessment of circadian variation in AV-nodal conduction during AF-Influence of rate control drugs.Frontiers in physiology · 2022Article
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
During atrial fibrillation (AF), the heart relies heavily on the atrio-ventricular (AV) node to regulate the heart rate. Thus, characterization of AV-nodal properties may provide valuable information for patient monitoring and prediction of rate control drug effects. In this work we present a network model consisting of the AV node, the bundle of His, and the Purkinje fibers, together with an associated workflow, for robust estimation of the model parameters from ECG. The model consists of two pathways, referred to as the slow and the fast pathway, interconnected at one end. Both pathways are composed of interacting nodes, with separate refractory periods and conduction delays determined by the stimulation history of each node. Together with this model, a fitness function based on the Poincaré plot accounting for dynamics in RR interval series and a problem specific genetic algorithm, are also presented. The robustness of the parameter estimates is evaluated using simulated data, based on clinical measurements from five AF patients. Results show that the proposed model and workflow could estimate the slow pathway parameters for the refractory period,
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