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Model-based Assessment of f-Wave Signal Quality in Patients with Atrial Fibrillation

Henriksson, Mikael LU ; Petrenas, Andrius ; Marozas, Vaidotas ; Sandberg, Frida LU and Sornmo, Leif LU (2018) In IEEE Transactions on Biomedical Engineering 65(11). p.2600-2611
Abstract

Objective: The detection and analysis of atrial fibrillation (AF) in the ECG is greatly influenced by signal quality. The present study proposes and evaluates a model-based f-wave signal quality index (SQI), denoted S, for use in the QRST-cancelled ECG signal. Methods: S is computed using a harmonic f-wave model, allowing for variation in frequency and amplitude. The properties of S are evaluated on both f-waves and P-waves using 378 12-lead ECGs, 1875 single-lead ECGs, and simulated signals. Results: S decreases monotonically when noise is added to f-wave signals, even for noise which overlaps spectrally with f-waves. Moreover, S is shown to be closely associated with the accuracy of AF frequency estimation, where S>0.3... (More)

Objective: The detection and analysis of atrial fibrillation (AF) in the ECG is greatly influenced by signal quality. The present study proposes and evaluates a model-based f-wave signal quality index (SQI), denoted S, for use in the QRST-cancelled ECG signal. Methods: S is computed using a harmonic f-wave model, allowing for variation in frequency and amplitude. The properties of S are evaluated on both f-waves and P-waves using 378 12-lead ECGs, 1875 single-lead ECGs, and simulated signals. Results: S decreases monotonically when noise is added to f-wave signals, even for noise which overlaps spectrally with f-waves. Moreover, S is shown to be closely associated with the accuracy of AF frequency estimation, where S>0.3 implies accurate estimation. When S is used as a measure of f-wave presence, AF detection performance improves: the sensitivity increases from 97.0% to 98.1% and the specificity increases from 97.4% to 97.8% when compared to the reference detector. Conclusion: The proposed SQI represents a novel approach to assessing f-wave signal quality, as well as to determining whether f-waves are present. Significance: The use of S improves the detection of AF and benefits the analysis of noisy ECGs.

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author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
AF detection, Atrial fibrillation (AF), Computational modeling, Detectors, ECG, Electrocardiography, Estimation, f-wave modeling, Frequency estimation, Harmonic analysis, Indexes, signal quality index (SQI)
in
IEEE Transactions on Biomedical Engineering
volume
65
issue
11
pages
2600 - 2611
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • pmid:29993509
  • scopus:85042875412
ISSN
1558-2531
DOI
10.1109/TBME.2018.2810508
project
Modelling and Quality Assessment of Atrial Fibrillatory Waves
language
English
LU publication?
yes
id
a53ff8ba-e0c3-4cdf-9186-4018ae54aaa0
date added to LUP
2018-03-16 15:21:47
date last changed
2022-05-22 20:27:46
@article{a53ff8ba-e0c3-4cdf-9186-4018ae54aaa0,
  abstract     = {{<p>Objective: The detection and analysis of atrial fibrillation (AF) in the ECG is greatly influenced by signal quality. The present study proposes and evaluates a model-based f-wave signal quality index (SQI), denoted S, for use in the QRST-cancelled ECG signal. Methods: S is computed using a harmonic f-wave model, allowing for variation in frequency and amplitude. The properties of S are evaluated on both f-waves and P-waves using 378 12-lead ECGs, 1875 single-lead ECGs, and simulated signals. Results: S decreases monotonically when noise is added to f-wave signals, even for noise which overlaps spectrally with f-waves. Moreover, S is shown to be closely associated with the accuracy of AF frequency estimation, where S&amp;#x003E;0.3 implies accurate estimation. When S is used as a measure of f-wave presence, AF detection performance improves: the sensitivity increases from 97.0% to 98.1% and the specificity increases from 97.4% to 97.8% when compared to the reference detector. Conclusion: The proposed SQI represents a novel approach to assessing f-wave signal quality, as well as to determining whether f-waves are present. Significance: The use of S improves the detection of AF and benefits the analysis of noisy ECGs.</p>}},
  author       = {{Henriksson, Mikael and Petrenas, Andrius and Marozas, Vaidotas and Sandberg, Frida and Sornmo, Leif}},
  issn         = {{1558-2531}},
  keywords     = {{AF detection; Atrial fibrillation (AF); Computational modeling; Detectors; ECG; Electrocardiography; Estimation; f-wave modeling; Frequency estimation; Harmonic analysis; Indexes; signal quality index (SQI)}},
  language     = {{eng}},
  month        = {{02}},
  number       = {{11}},
  pages        = {{2600--2611}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{IEEE Transactions on Biomedical Engineering}},
  title        = {{Model-based Assessment of f-Wave Signal Quality in Patients with Atrial Fibrillation}},
  url          = {{http://dx.doi.org/10.1109/TBME.2018.2810508}},
  doi          = {{10.1109/TBME.2018.2810508}},
  volume       = {{65}},
  year         = {{2018}},
}