Statistical modeling of atrioventricular nodal function during atrial fibrillation: An update

Valentina D A Corino, Frida Sandberg, Federico Lombardi, Luca T. Mainardi, Leif Sornmo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper introduces a number of advancements of our recently proposed model of atrioventricular (AV) node function during atrial fibrillation (AF). The model is defined by parameters characterizing the arrival rate of atrial impulses, the probability of an impulse choosing either one of the two AV nodal pathways, the refractory periods of these pathways, and their prolongation. In the updated model, the characterization of AV nodal pathways is made more detailed and the number of pathways is determined by the Bayesian information criterion. The performance is evaluated on ECG data acquired from twenty-five AF patients during rest and head-up tilt test. The results show that the refined AV node model provides significantly better fit than did the original model. During tilt, the AF frequency increased (6.25 ±0.58 Hz vs. 6.32 ±0.61 Hz, p <0.05, rest vs. tilt) and the prolongation of the refractory periods decreased for both pathways (slow pathway: 0.23 ±0.20 s vs. 0.11 ±0.10 s, p <0.001, rest vs. tilt; fast pathway: 0.24±0.31 s vs. 0.16±0.19 s, p <0.05, rest vs. tilt). These results show that AV node characteristics can be assessed noninvasively for the purpose of quantifying changes induced by autonomic stimulation.

Original languageEnglish
Title of host publicationBIOSIGNALS 2013 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing
Pages25-29
Number of pages5
Publication statusPublished - 2013
EventInternational Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2013 - Barcelona, Spain
Duration: Feb 11 2013Feb 14 2013

Other

OtherInternational Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2013
CountrySpain
CityBarcelona
Period2/11/132/14/13

Keywords

  • Atrial fibrillation
  • Atrioventricular node
  • Maximum likelihood estimation
  • Statistical modeling

ASJC Scopus subject areas

  • Biomedical Engineering
  • Signal Processing

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  • Cite this

    Corino, V. D. A., Sandberg, F., Lombardi, F., Mainardi, L. T., & Sornmo, L. (2013). Statistical modeling of atrioventricular nodal function during atrial fibrillation: An update. In BIOSIGNALS 2013 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing (pp. 25-29)