Low-complexity detection of atrial fibrillation in continuous long-term monitoring.
(2015) In Computers in Biology and Medicine 65(Online 28 January 2015). p.184-191- Abstract
- This study describes an atrial fibrillation (AF) detector whose structure is well-adapted both for detection of subclinical AF episodes and for implementation in a battery-powered device for use in continuous long-term monitoring applications. A key aspect for achieving these two properties is the use of an 8-beat sliding window, which thus is much shorter than the 128-beat window used in most existing AF detectors. The building blocks of the proposed detector include ectopic beat filtering, bigeminal suppression, characterization of RR interval irregularity, and signal fusion. With one design parameter, the performance can be tuned to put more emphasis on avoiding false alarms due to non-AF arrhythmias or more emphasis on detecting brief... (More)
- This study describes an atrial fibrillation (AF) detector whose structure is well-adapted both for detection of subclinical AF episodes and for implementation in a battery-powered device for use in continuous long-term monitoring applications. A key aspect for achieving these two properties is the use of an 8-beat sliding window, which thus is much shorter than the 128-beat window used in most existing AF detectors. The building blocks of the proposed detector include ectopic beat filtering, bigeminal suppression, characterization of RR interval irregularity, and signal fusion. With one design parameter, the performance can be tuned to put more emphasis on avoiding false alarms due to non-AF arrhythmias or more emphasis on detecting brief AF episodes. Despite its very simple structure, the results show that the detector performs better on the MIT-BIH Atrial Fibrillation database than do existing detectors, with high sensitivity and specificity (97.1% and 98.3%, respectively). The detector can be implemented with just a few arithmetical operations and does not require a large memory buffer thanks to the short window. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/5144928
- author
- Petrėnas, Andrius ; Marozas, Vaidotas and Sörnmo, Leif LU
- organization
- publishing date
- 2015
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Computers in Biology and Medicine
- volume
- 65
- issue
- Online 28 January 2015
- pages
- 184 - 191
- publisher
- Elsevier
- external identifiers
-
- pmid:25666902
- wos:000362860700022
- scopus:84942366412
- pmid:25666902
- ISSN
- 1879-0534
- DOI
- 10.1016/j.compbiomed.2015.01.019
- language
- English
- LU publication?
- yes
- id
- 886dead0-b11c-46e3-9dc8-50bbaa6b1674 (old id 5144928)
- date added to LUP
- 2016-04-01 10:50:16
- date last changed
- 2022-04-28 01:51:08
@article{886dead0-b11c-46e3-9dc8-50bbaa6b1674,
abstract = {{This study describes an atrial fibrillation (AF) detector whose structure is well-adapted both for detection of subclinical AF episodes and for implementation in a battery-powered device for use in continuous long-term monitoring applications. A key aspect for achieving these two properties is the use of an 8-beat sliding window, which thus is much shorter than the 128-beat window used in most existing AF detectors. The building blocks of the proposed detector include ectopic beat filtering, bigeminal suppression, characterization of RR interval irregularity, and signal fusion. With one design parameter, the performance can be tuned to put more emphasis on avoiding false alarms due to non-AF arrhythmias or more emphasis on detecting brief AF episodes. Despite its very simple structure, the results show that the detector performs better on the MIT-BIH Atrial Fibrillation database than do existing detectors, with high sensitivity and specificity (97.1% and 98.3%, respectively). The detector can be implemented with just a few arithmetical operations and does not require a large memory buffer thanks to the short window.}},
author = {{Petrėnas, Andrius and Marozas, Vaidotas and Sörnmo, Leif}},
issn = {{1879-0534}},
language = {{eng}},
number = {{Online 28 January 2015}},
pages = {{184--191}},
publisher = {{Elsevier}},
series = {{Computers in Biology and Medicine}},
title = {{Low-complexity detection of atrial fibrillation in continuous long-term monitoring.}},
url = {{http://dx.doi.org/10.1016/j.compbiomed.2015.01.019}},
doi = {{10.1016/j.compbiomed.2015.01.019}},
volume = {{65}},
year = {{2015}},
}