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Statistical Modeling of Atrioventricular Nodal Function During Atrial Fibrillation Focusing on the Refractory Period Estimation

Corino, Valentina D. A. ; Sandberg, Frida LU ; Lombardi, Federico ; Mainardi, Luca T. and Sörnmo, Leif LU (2014) 6th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) 452. p.258-268
Abstract
We have recently proposed a statistical AV node model defined by a set of parameters characterizing the arrival rate of atrial impulses, the probability of an impulse passing through the fast or the slow pathway, the refractory periods of the pathways, and the prolongation of refractory periods. All parameters are estimated from the RR interval series using maximum likelihood (ML) estimation, except for the mean arrival rate of atrial impulses which is estimated by the AF frequency derived from the f-waves. In this chapter, we compare four different methods, based either on the Poincare plot or ML estimation, for determining the refractory period of the slow pathway. Simulation results show better performance of the ML estimator,... (More)
We have recently proposed a statistical AV node model defined by a set of parameters characterizing the arrival rate of atrial impulses, the probability of an impulse passing through the fast or the slow pathway, the refractory periods of the pathways, and the prolongation of refractory periods. All parameters are estimated from the RR interval series using maximum likelihood (ML) estimation, except for the mean arrival rate of atrial impulses which is estimated by the AF frequency derived from the f-waves. In this chapter, we compare four different methods, based either on the Poincare plot or ML estimation, for determining the refractory period of the slow pathway. Simulation results show better performance of the ML estimator, especially in the presence of artifacts due to premature ventricular beats or misdetected beats. The performance was also evaluated on ECG data acquired from 26 AF patients during rest and head-up tilt test. During tilt, the AF frequency increased (6.08 +/- 1.03 Hz vs. 6.20 +/- 0.99 Hz, p < 0.05, rest vs. tilt) and the refractory periods of both pathways decreased (slow pathway: 0.43 +/- 0.12 s vs. 0.38 +/- 0.12 s, p = 0.001, rest vs. tilt; fast pathway: 0.55 +/- 0.14 s vs. 0.47 +/- 0.11 s, p < 0.05, rest vs. tilt). These results show that AV node characteristics can be assessed non-invasively to quantify changes induced by autonomic stimulation. (Less)
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author
; ; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Atrial fibrillation, Atrioventricular node, Statistical modeling, Maximum likelihood estimation
host publication
Biomedical Engineering Systems and Technologies (Biostec 2013)
volume
452
pages
258 - 268
publisher
Springer
conference name
6th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC)
conference location
Barcelona, Spain
conference dates
2013-02-11 - 2013-02-14
external identifiers
  • wos:000358524500018
  • scopus:84916208159
ISSN
1865-0929
DOI
10.1007/978-3-662-44485-6_18
language
English
LU publication?
yes
id
c71dc03d-57b4-4bd1-929d-effe30e834a3 (old id 7773600)
date added to LUP
2016-04-01 13:33:23
date last changed
2022-01-27 19:47:33
@inproceedings{c71dc03d-57b4-4bd1-929d-effe30e834a3,
  abstract     = {{We have recently proposed a statistical AV node model defined by a set of parameters characterizing the arrival rate of atrial impulses, the probability of an impulse passing through the fast or the slow pathway, the refractory periods of the pathways, and the prolongation of refractory periods. All parameters are estimated from the RR interval series using maximum likelihood (ML) estimation, except for the mean arrival rate of atrial impulses which is estimated by the AF frequency derived from the f-waves. In this chapter, we compare four different methods, based either on the Poincare plot or ML estimation, for determining the refractory period of the slow pathway. Simulation results show better performance of the ML estimator, especially in the presence of artifacts due to premature ventricular beats or misdetected beats. The performance was also evaluated on ECG data acquired from 26 AF patients during rest and head-up tilt test. During tilt, the AF frequency increased (6.08 +/- 1.03 Hz vs. 6.20 +/- 0.99 Hz, p &lt; 0.05, rest vs. tilt) and the refractory periods of both pathways decreased (slow pathway: 0.43 +/- 0.12 s vs. 0.38 +/- 0.12 s, p = 0.001, rest vs. tilt; fast pathway: 0.55 +/- 0.14 s vs. 0.47 +/- 0.11 s, p &lt; 0.05, rest vs. tilt). These results show that AV node characteristics can be assessed non-invasively to quantify changes induced by autonomic stimulation.}},
  author       = {{Corino, Valentina D. A. and Sandberg, Frida and Lombardi, Federico and Mainardi, Luca T. and Sörnmo, Leif}},
  booktitle    = {{Biomedical Engineering Systems and Technologies (Biostec 2013)}},
  issn         = {{1865-0929}},
  keywords     = {{Atrial fibrillation; Atrioventricular node; Statistical modeling; Maximum likelihood estimation}},
  language     = {{eng}},
  pages        = {{258--268}},
  publisher    = {{Springer}},
  title        = {{Statistical Modeling of Atrioventricular Nodal Function During Atrial Fibrillation Focusing on the Refractory Period Estimation}},
  url          = {{http://dx.doi.org/10.1007/978-3-662-44485-6_18}},
  doi          = {{10.1007/978-3-662-44485-6_18}},
  volume       = {{452}},
  year         = {{2014}},
}