Signal quality assessment of f-waves in atrial fibrillation
(2017) In Computing in Cardiology 44.- Abstract
Ambulatory ECG recordings are frequently corrupted by artifacts caused by, e.g., muscle activity or moving electrodes, which complicates the analysis of f-waves and motivates signal quality assessment to improve the reliability of f-wave analysis. Although many methods have been developed for assessing the quality of ECG signals in general, no method deals specifically with f-waves. This study proposes a novel signal quality index (SQI), using a modelbased approach for assessment of f-wave signal quality. To evaluate the performance of the SQI, 189 5-s recordings of f-waves from AF patients are studied, as is the same number of recordings with motion artifacts and electrode movements taken from the MIT-BIH Noise Stress Test Database.... (More)
Ambulatory ECG recordings are frequently corrupted by artifacts caused by, e.g., muscle activity or moving electrodes, which complicates the analysis of f-waves and motivates signal quality assessment to improve the reliability of f-wave analysis. Although many methods have been developed for assessing the quality of ECG signals in general, no method deals specifically with f-waves. This study proposes a novel signal quality index (SQI), using a modelbased approach for assessment of f-wave signal quality. To evaluate the performance of the SQI, 189 5-s recordings of f-waves from AF patients are studied, as is the same number of recordings with motion artifacts and electrode movements taken from the MIT-BIH Noise Stress Test Database. The signal quality index is capable of discriminating between f-waves and noisy recordings with an accuracy of 98%. The results suggest that the proposed signal quality index correctly identifies noisy recordings, and can be used to improve the reliability of f-wave analysis.
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- author
- Henriksson, Mikael LU ; Petrenas, Andrius; Marozas, Vaidotas; Sandberg, Frida LU and Sörnmo, Leif LU
- organization
- publishing date
- 2017-01-01
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Computing in Cardiology
- volume
- 44
- pages
- 4 pages
- publisher
- IEEE Computer Society
- external identifiers
-
- scopus:85045113529
- ISSN
- 2325-8861
- DOI
- 10.22489/CinC.2017.051-153
- language
- English
- LU publication?
- yes
- id
- a6c74b16-3abd-4753-b653-adad0a8c2150
- date added to LUP
- 2018-04-17 08:28:42
- date last changed
- 2018-11-21 21:39:22
@article{a6c74b16-3abd-4753-b653-adad0a8c2150,
abstract = {<p>Ambulatory ECG recordings are frequently corrupted by artifacts caused by, e.g., muscle activity or moving electrodes, which complicates the analysis of f-waves and motivates signal quality assessment to improve the reliability of f-wave analysis. Although many methods have been developed for assessing the quality of ECG signals in general, no method deals specifically with f-waves. This study proposes a novel signal quality index (SQI), using a modelbased approach for assessment of f-wave signal quality. To evaluate the performance of the SQI, 189 5-s recordings of f-waves from AF patients are studied, as is the same number of recordings with motion artifacts and electrode movements taken from the MIT-BIH Noise Stress Test Database. The signal quality index is capable of discriminating between f-waves and noisy recordings with an accuracy of 98%. The results suggest that the proposed signal quality index correctly identifies noisy recordings, and can be used to improve the reliability of f-wave analysis.</p>},
author = {Henriksson, Mikael and Petrenas, Andrius and Marozas, Vaidotas and Sandberg, Frida and Sörnmo, Leif},
issn = {2325-8861},
language = {eng},
month = {01},
pages = {4},
publisher = {IEEE Computer Society},
series = {Computing in Cardiology},
title = {Signal quality assessment of f-waves in atrial fibrillation},
url = {http://dx.doi.org/10.22489/CinC.2017.051-153},
volume = {44},
year = {2017},
}