Organization tracking of long-term atrial fibrillation recordings: differences between paroxysmal and persistent episodes
(2009) 36th Annual Computers in Cardiology Conference, 2009 36. p.509-512- Abstract
- In this work, a method for non-invasive assessment of
AF organization has been applied to discriminating between
paroxysmal and long-term persistent AF episodes.
Following extraction of the atrial activity (AA) signal,
the dominant atrial frequency (DAF) of the AA was computed
based on a hidden Markov model. Finally, the main
atrial wave (MAW) was obtained by bandpass filtering
centered on the DAF, thus providing a time series suitable
for AF organization estimation with sample entropy
(SampEn). The performance of the method was evaluated
on 24-h Holter recordings with long-term changes
in AF organization. The results showed that episodes... (More) - In this work, a method for non-invasive assessment of
AF organization has been applied to discriminating between
paroxysmal and long-term persistent AF episodes.
Following extraction of the atrial activity (AA) signal,
the dominant atrial frequency (DAF) of the AA was computed
based on a hidden Markov model. Finally, the main
atrial wave (MAW) was obtained by bandpass filtering
centered on the DAF, thus providing a time series suitable
for AF organization estimation with sample entropy
(SampEn). The performance of the method was evaluated
on 24-h Holter recordings with long-term changes
in AF organization. The results showed that episodes of
paroxysmal AF (0.06930.0147) were consistently associated
with lower SampEn than episodes with persistent
AF (0.10560.0146). Moreover, 94.2% of 1-min segments
with paroxysmal AF and 88.6% of 1-min segments with
persistent AF could be correctly classified based on Samp-
En information, thus making it possible to classify longterm
recordings of patients without AF history. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1511403
- author
- Alcaraz, Raul ; Sandberg, Frida LU ; Sörnmo, Leif LU and Rieta, JJ
- organization
- publishing date
- 2009
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- [Host publication title missing]
- volume
- 36
- pages
- 509 - 512
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 36th Annual Computers in Cardiology Conference, 2009
- conference location
- Park City, UT, United States
- conference dates
- 2009-09-13 - 2009-09-16
- external identifiers
-
- scopus:77952772601
- language
- English
- LU publication?
- yes
- id
- 8213bdca-b571-4da4-96fd-25a9cdbf703d (old id 1511403)
- alternative location
- http://www.cinc.org/archives/2009/pdf/0509.pdf
- date added to LUP
- 2016-04-04 11:58:59
- date last changed
- 2022-01-29 22:41:55
@inproceedings{8213bdca-b571-4da4-96fd-25a9cdbf703d,
abstract = {{In this work, a method for non-invasive assessment of<br/><br>
AF organization has been applied to discriminating between<br/><br>
paroxysmal and long-term persistent AF episodes.<br/><br>
Following extraction of the atrial activity (AA) signal,<br/><br>
the dominant atrial frequency (DAF) of the AA was computed<br/><br>
based on a hidden Markov model. Finally, the main<br/><br>
atrial wave (MAW) was obtained by bandpass filtering<br/><br>
centered on the DAF, thus providing a time series suitable<br/><br>
for AF organization estimation with sample entropy<br/><br>
(SampEn). The performance of the method was evaluated<br/><br>
on 24-h Holter recordings with long-term changes<br/><br>
in AF organization. The results showed that episodes of<br/><br>
paroxysmal AF (0.06930.0147) were consistently associated<br/><br>
with lower SampEn than episodes with persistent<br/><br>
AF (0.10560.0146). Moreover, 94.2% of 1-min segments<br/><br>
with paroxysmal AF and 88.6% of 1-min segments with<br/><br>
persistent AF could be correctly classified based on Samp-<br/><br>
En information, thus making it possible to classify longterm<br/><br>
recordings of patients without AF history.}},
author = {{Alcaraz, Raul and Sandberg, Frida and Sörnmo, Leif and Rieta, JJ}},
booktitle = {{[Host publication title missing]}},
language = {{eng}},
pages = {{509--512}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Organization tracking of long-term atrial fibrillation recordings: differences between paroxysmal and persistent episodes}},
url = {{http://www.cinc.org/archives/2009/pdf/0509.pdf}},
volume = {{36}},
year = {{2009}},
}