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Statistical modeling of the atrioventricular node during atrial fibrillation : Data length and estimator performance

Corino, Valentina D.A.; Sandberg, Frida LU ; Mainardi, Luca T. and Sornmo, Leif LU (2013) 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 p.2567-2570
Abstract

The atrioventricular (AV) node plays a central role during atrial fibrillation (AF). We have recently proposed a statistical AV node model defined by parameters characterizing the arrival rate of atrial impulses, the probability of an impulse choosing either one of the dual AV nodal pathways, the refractory periods of the pathways, and the prolongation of refractory periods. All model parameters are estimated from the RR 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. The aim of this study is to present a unified approach to ML estimation which also involves the shorter refractory period, thus avoiding our previous... (More)

The atrioventricular (AV) node plays a central role during atrial fibrillation (AF). We have recently proposed a statistical AV node model defined by parameters characterizing the arrival rate of atrial impulses, the probability of an impulse choosing either one of the dual AV nodal pathways, the refractory periods of the pathways, and the prolongation of refractory periods. All model parameters are estimated from the RR 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. The aim of this study is to present a unified approach to ML estimation which also involves the shorter refractory period, thus avoiding our previous Poincaré plot analysis which becomes biased. In addition, the number of RR intervals required for accurate parameter estimation is presented. The results show that the shorter refractory period can be accurately estimated, and that the resulting estimates converge to the true values when about 500 RR intervals are available.

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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
RR series interval, poincare plot analysis, atrioventricular node refactory period, f-wave, atrial fibrillation frequency, Maximum likelihood estimation, paramameter estimation, atrial impulse probability, atrial impulse arrival rate, statistical atrioventricular node model, data estimator performance, data length performance
host publication
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
pages
4 pages
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
conference location
Osaka, Japan
conference dates
2013-07-03 - 2013-07-07
external identifiers
  • scopus:84886497447
ISBN
9781457702167
DOI
10.1109/EMBC.2013.6610064
language
English
LU publication?
yes
id
8e724d24-aea7-4c37-84f6-76f2b2212102
date added to LUP
2019-06-04 15:45:29
date last changed
2019-07-02 04:47:21
@inproceedings{8e724d24-aea7-4c37-84f6-76f2b2212102,
  abstract     = {<p>The atrioventricular (AV) node plays a central role during atrial fibrillation (AF). We have recently proposed a statistical AV node model defined by parameters characterizing the arrival rate of atrial impulses, the probability of an impulse choosing either one of the dual AV nodal pathways, the refractory periods of the pathways, and the prolongation of refractory periods. All model parameters are estimated from the RR 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. The aim of this study is to present a unified approach to ML estimation which also involves the shorter refractory period, thus avoiding our previous Poincaré plot analysis which becomes biased. In addition, the number of RR intervals required for accurate parameter estimation is presented. The results show that the shorter refractory period can be accurately estimated, and that the resulting estimates converge to the true values when about 500 RR intervals are available.</p>},
  author       = {Corino, Valentina D.A. and Sandberg, Frida and Mainardi, Luca T. and Sornmo, Leif},
  isbn         = {9781457702167},
  keyword      = {RR series interval,poincare plot analysis,atrioventricular node refactory period,f-wave,atrial fibrillation frequency,Maximum likelihood estimation,paramameter estimation,atrial impulse probability,atrial impulse arrival rate,statistical atrioventricular node model,data estimator performance,data length performance},
  language     = {eng},
  location     = {Osaka, Japan},
  month        = {10},
  pages        = {2567--2570},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Statistical modeling of the atrioventricular node during atrial fibrillation : Data length and estimator performance},
  url          = {http://dx.doi.org/10.1109/EMBC.2013.6610064},
  year         = {2013},
}