Advanced

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

Corino, Valentina D A; Sandberg, Frida LU ; Lombardi, Federico; Mainardi, Luca T. and Sornmo, Leif LU (2013) International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2013 In BIOSIGNALS 2013 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing p.25-29
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... (More)

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.

(Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Atrial fibrillation, Atrioventricular node, Maximum likelihood estimation, Statistical modeling
in
BIOSIGNALS 2013 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing
pages
5 pages
conference name
International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2013
external identifiers
  • scopus:84877932190
ISBN
9789898565365
language
English
LU publication?
yes
id
52e0614b-5000-4e0b-9d9a-9af73835c669
date added to LUP
2017-08-09 15:43:42
date last changed
2018-01-07 12:14:21
@inproceedings{52e0614b-5000-4e0b-9d9a-9af73835c669,
  abstract     = {<p>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 &lt; 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 &lt; 0.001, rest vs. tilt; fast pathway: 0.24±0.31 s vs. 0.16±0.19 s, p &lt; 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.</p>},
  author       = {Corino, Valentina D A and Sandberg, Frida and Lombardi, Federico and Mainardi, Luca T. and Sornmo, Leif},
  booktitle    = {BIOSIGNALS 2013 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing},
  isbn         = {9789898565365},
  keyword      = {Atrial fibrillation,Atrioventricular node,Maximum likelihood estimation,Statistical modeling},
  language     = {eng},
  pages        = {25--29},
  title        = {Statistical modeling of atrioventricular nodal function during atrial fibrillation : An update},
  year         = {2013},
}