A novel statistical model of the dual pathway atrioventricular node during atrial fibrillation
(2016) 42nd Computing in Cardiology Conference, 2015 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.
(Less)
- author
- Henriksson, Mikael LU ; Corino, Valentina D A ; Sörnmo, Leif LU and Sandberg, Frida LU
- organization
- publishing date
- 2016-02-16
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Computing in Cardiology
- volume
- 42
- article number
- 7408689
- pages
- 4 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 42nd Computing in Cardiology Conference, 2015
- conference location
- Nice, France
- conference dates
- 2015-09-06 - 2015-09-09
- external identifiers
-
- scopus:84964066196
- ISBN
- 9781509006854
- DOI
- 10.1109/CIC.2015.7408689
- project
- Modelling and Quality Assessment of Atrial Fibrillatory Waves
- language
- English
- LU publication?
- yes
- id
- c9e07c15-497e-4616-9c8a-cfcedf40a357
- date added to LUP
- 2016-06-28 14:39:47
- date last changed
- 2022-01-30 04:47:57
@inproceedings{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}}, booktitle = {{Computing in Cardiology}}, isbn = {{9781509006854}}, language = {{eng}}, month = {{02}}, pages = {{473--476}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{A novel statistical model of the dual pathway atrioventricular node during atrial fibrillation}}, url = {{http://dx.doi.org/10.1109/CIC.2015.7408689}}, doi = {{10.1109/CIC.2015.7408689}}, volume = {{42}}, year = {{2016}}, }