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A novel statistical model of the dual pathway atrioventricular node during atrial fibrillation

Henriksson, Mikael LU ; Corino, Valentina D A; Sörnmo, Leif LU and Sandberg, Frida LU (2016) 42nd Computing in Cardiology Conference, 2015 In Computing in Cardiology 42. p.473-476
Abstract

The atrioventricular (AV) node plays an important role during atrial fibrillation (AF). In particular, the refractoriness of its cells influences the conduction of atrial impulses to the ventricles and, thus, the ventricular response. This study introduces a novel statistical model of the AV node, accounting for pathway switching, which can be used for non-invasive assessment of the refractory properties of the slow and the fast AV nodal pathway during AF, using the atrial fibrillatory rate and the series of RR intervals obtained from the ECG. A number of simulated histograms is presented, illustrating that even though only four parameters are used to characterize the AV node, the model is capable of representing a wide range of... (More)

The atrioventricular (AV) node plays an important role during atrial fibrillation (AF). In particular, the refractoriness of its cells influences the conduction of atrial impulses to the ventricles and, thus, the ventricular response. This study introduces a novel statistical model of the AV node, accounting for pathway switching, which can be used for non-invasive assessment of the refractory properties of the slow and the fast AV nodal pathway during AF, using the atrial fibrillatory rate and the series of RR intervals obtained from the ECG. A number of simulated histograms is presented, illustrating that even though only four parameters are used to characterize the AV node, the model is capable of representing a wide range of different RR interval series. Estimation of model parameters is evaluated with simulated RR interval series. It is shown that a signal consisting of 2400 RR intervals is sufficient for accurate parameter estimation, with an average estimation error less than 50 ms in all parameters. It is concluded that the model offers a novel way to obtain information regarding AV nodal refractoriness from the ECG.

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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
Computing in Cardiology
volume
42
pages
4 pages
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
42nd Computing in Cardiology Conference, 2015
external identifiers
  • Scopus:84964066196
ISBN
9781509006854
DOI
10.1109/CIC.2015.7408689
language
English
LU publication?
yes
id
c9e07c15-497e-4616-9c8a-cfcedf40a357
date added to LUP
2016-06-28 14:39:47
date last changed
2016-06-28 14:45:13
@misc{c9e07c15-497e-4616-9c8a-cfcedf40a357,
  abstract     = {<p>The atrioventricular (AV) node plays an important role during atrial fibrillation (AF). In particular, the refractoriness of its cells influences the conduction of atrial impulses to the ventricles and, thus, the ventricular response. This study introduces a novel statistical model of the AV node, accounting for pathway switching, which can be used for non-invasive assessment of the refractory properties of the slow and the fast AV nodal pathway during AF, using the atrial fibrillatory rate and the series of RR intervals obtained from the ECG. A number of simulated histograms is presented, illustrating that even though only four parameters are used to characterize the AV node, the model is capable of representing a wide range of different RR interval series. Estimation of model parameters is evaluated with simulated RR interval series. It is shown that a signal consisting of 2400 RR intervals is sufficient for accurate parameter estimation, with an average estimation error less than 50 ms in all parameters. It is concluded that the model offers a novel way to obtain information regarding AV nodal refractoriness from the ECG.</p>},
  author       = {Henriksson, Mikael and Corino, Valentina D A and Sörnmo, Leif and Sandberg, Frida},
  isbn         = {9781509006854},
  language     = {eng},
  month        = {02},
  pages        = {473--476},
  publisher    = {ARRAY(0xbba3008)},
  series       = {Computing in Cardiology},
  title        = {A novel statistical model of the dual pathway atrioventricular node during atrial fibrillation},
  url          = {http://dx.doi.org/10.1109/CIC.2015.7408689},
  volume       = {42},
  year         = {2016},
}