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Improved Time-Frequency Analysis of Atrial Fibrillation Signals Using Spectral Modeling

Corino, Valentina D. A. ; Mainardi, Luca T. ; Stridh, Martin LU and Sörnmo, Leif LU (2008) In IEEE Transactions on Biomedical Engineering 55(12). p.2723-2730
Abstract
In patients with atrial fibrillation (AF), the fibrillatory frequency trend and the time-dependent spectral characteristics can be investigated using a spectral profile technique. The spectral profile is updated by fitting each short-time spectrum. The aim of this study is to develop model-based means for stricter control on the update of the spectral profile. A spectral model defined by a superposition of Gaussian functions is suggested for describing the fundamental and harmonics of the atrial waves during AF, thereby accounting for basic characteristics of the typical AF spectrum. The model parameters are obtained from weighted least squares fitting of the model to the observed spectrum. The method was tested on simulated signals as... (More)
In patients with atrial fibrillation (AF), the fibrillatory frequency trend and the time-dependent spectral characteristics can be investigated using a spectral profile technique. The spectral profile is updated by fitting each short-time spectrum. The aim of this study is to develop model-based means for stricter control on the update of the spectral profile. A spectral model defined by a superposition of Gaussian functions is suggested for describing the fundamental and harmonics of the atrial waves during AF, thereby accounting for basic characteristics of the typical AF spectrum. The model parameters are obtained from weighted least squares fitting of the model to the observed spectrum. The method was tested on simulated signals as well as on 48 ECG recordings from 15 patients with persistent AF. Using simulated signals, we assessed the accuracy in terms of magnitude and width or the spectral peaks. For SNR = 0 dB, the maximum normalized error was less than 0.2 when estimating magnitude of both the fundamental and the harmonics, whereas it was less than 0.15 for the fundamental and 0.7 for the harmonics with respect to the estimation of the width. We observed a marked Improvement while tracking the main fibrillatory frequency as the error was reduced by more than 50% In comparison with the original method. Analyzing ECGs, reliable spectral profiles were obtained In all recordings, even In those cases (5/48) that were not well characterized by the original method. (Less)
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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
fibrillatory frequency, Gaussian, time-frequency analysis, functions, Atrial fibrillation (AF), ECG
in
IEEE Transactions on Biomedical Engineering
volume
55
issue
12
pages
2723 - 2730
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • wos:000262541400005
  • scopus:57349154551
  • pmid:19126451
ISSN
1558-2531
DOI
10.1109/TBME.2008.2002158
language
English
LU publication?
yes
id
4bfe6035-7f9e-42d6-bbd3-5d933f5c0a85 (old id 1376023)
date added to LUP
2016-04-01 13:56:14
date last changed
2022-01-27 22:00:22
@article{4bfe6035-7f9e-42d6-bbd3-5d933f5c0a85,
  abstract     = {{In patients with atrial fibrillation (AF), the fibrillatory frequency trend and the time-dependent spectral characteristics can be investigated using a spectral profile technique. The spectral profile is updated by fitting each short-time spectrum. The aim of this study is to develop model-based means for stricter control on the update of the spectral profile. A spectral model defined by a superposition of Gaussian functions is suggested for describing the fundamental and harmonics of the atrial waves during AF, thereby accounting for basic characteristics of the typical AF spectrum. The model parameters are obtained from weighted least squares fitting of the model to the observed spectrum. The method was tested on simulated signals as well as on 48 ECG recordings from 15 patients with persistent AF. Using simulated signals, we assessed the accuracy in terms of magnitude and width or the spectral peaks. For SNR = 0 dB, the maximum normalized error was less than 0.2 when estimating magnitude of both the fundamental and the harmonics, whereas it was less than 0.15 for the fundamental and 0.7 for the harmonics with respect to the estimation of the width. We observed a marked Improvement while tracking the main fibrillatory frequency as the error was reduced by more than 50% In comparison with the original method. Analyzing ECGs, reliable spectral profiles were obtained In all recordings, even In those cases (5/48) that were not well characterized by the original method.}},
  author       = {{Corino, Valentina D. A. and Mainardi, Luca T. and Stridh, Martin and Sörnmo, Leif}},
  issn         = {{1558-2531}},
  keywords     = {{fibrillatory frequency; Gaussian; time-frequency analysis; functions; Atrial fibrillation (AF); ECG}},
  language     = {{eng}},
  number       = {{12}},
  pages        = {{2723--2730}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{IEEE Transactions on Biomedical Engineering}},
  title        = {{Improved Time-Frequency Analysis of Atrial Fibrillation Signals Using Spectral Modeling}},
  url          = {{http://dx.doi.org/10.1109/TBME.2008.2002158}},
  doi          = {{10.1109/TBME.2008.2002158}},
  volume       = {{55}},
  year         = {{2008}},
}