Changes in RR Series Characteristics during Atrial Fibrillation: An AV Node Simulation Study

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The atrioventricular node (AVN) plays an important role in rate control during atrial fibrillation (AF). To further our understanding of the AVN function in AF, we present a model-based study, relating AVN electrophysiological characteristics to changes in RR series characteristics observed during treatment with rate control drugs. The dual-pathway physiology of the AVN was modelled using a network of nodes. The atrial impulse series was modelled with a Pearson Type IV distribution. Simulations were performed with randomly generated model parameters based on clinically observed ranges and the heart rate, variability and irregularity of the resulting RR series were quantified by their mean, rmssd and sample entropy, respectively. Analysis using linear regression showed that an increase in the RR mean was predominantly associated with an increase in the refractory period of the slow pathway, whereas changes in RR variability and RR irregularity were associated with changes in conduction delay. Notably, changes in the mean and standard deviation of the atrial impulse intervals were associated with changes in RR irregularity but not with changes in RR variability. Our results suggest that changes in RR series dynamics observed in response to rate control drugs reflect changes in the atrial electrical activity and AV conduction delay, however the results needs to be verified with clinical data.

Original languageEnglish
Title of host publication2021 Computing in Cardiology, CinC 2021
PublisherIEEE Computer Society
ISBN (Electronic)9781665479165
ISBN (Print)9781665467216
Publication statusPublished - 2021
Event2021 Computing in Cardiology, CinC 2021 - Brno, Czech Republic
Duration: 2021 Sept 132021 Sept 15

Publication series

NameComputing in Cardiology
ISSN (Print)2325-8861
ISSN (Electronic)2325-887X


Conference2021 Computing in Cardiology, CinC 2021
Country/TerritoryCzech Republic

Bibliographical note

Publisher Copyright:
© 2021 Creative Commons.

Subject classification (UKÄ)

  • Medical Biotechnology
  • Medical Biotechnology


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