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Spindles in Svarog: framework and software for parametrization of EEG transients
We present a complete framework for time-frequency parametrization of EEG transients, based upon matching pursuit (MP) decomposition, applied to the detection of sleep spindles. Ranges of spindles duration (>0.5 s) and frequency (11–16 Hz) are taken directly from their standard definitions. Minim...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4424848/ https://www.ncbi.nlm.nih.gov/pubmed/26005412 http://dx.doi.org/10.3389/fnhum.2015.00258 |
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author | Durka, Piotr J. Malinowska, Urszula Zieleniewska, Magdalena O'Reilly, Christian Różański, Piotr T. Żygierewicz, Jarosław |
author_facet | Durka, Piotr J. Malinowska, Urszula Zieleniewska, Magdalena O'Reilly, Christian Różański, Piotr T. Żygierewicz, Jarosław |
author_sort | Durka, Piotr J. |
collection | PubMed |
description | We present a complete framework for time-frequency parametrization of EEG transients, based upon matching pursuit (MP) decomposition, applied to the detection of sleep spindles. Ranges of spindles duration (>0.5 s) and frequency (11–16 Hz) are taken directly from their standard definitions. Minimal amplitude is computed from the distribution of the root mean square (RMS) amplitude of the signal within the frequency band of sleep spindles. Detection algorithm depends on the choice of just one free parameter, which is a percentile of this distribution. Performance of detection is assessed on the first cohort/second subset of the Montreal Archive of Sleep Studies (MASS-C1/SS2). Cross-validation performed on the 19 available overnight recordings returned the optimal percentile of the RMS distribution close to 97 in most cases, and the following overall performance measures: sensitivity 0.63 ± 0.06, positive predictive value 0.47 ± 0.08, and Matthews coefficient of correlation 0.51 ± 0.04. These concordances are similar to the results achieved on this database by other automatic methods. Proposed detailed parametrization of sleep spindles within a universal framework, encompassing also other EEG transients, opens new possibilities of high resolution investigation of their relations and detailed characteristics. MP decomposition, selection of relevant structures, and simple creation of EEG profiles used previously for assessment of brain activity of patients in disorders of consciousness are implemented in a freely available software package Svarog (Signal Viewer, Analyzer and Recorder On GPL) with user-friendly, mouse-driven interface for review and analysis of EEG. Svarog can be downloaded from http://braintech.pl/svarog. |
format | Online Article Text |
id | pubmed-4424848 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-44248482015-05-22 Spindles in Svarog: framework and software for parametrization of EEG transients Durka, Piotr J. Malinowska, Urszula Zieleniewska, Magdalena O'Reilly, Christian Różański, Piotr T. Żygierewicz, Jarosław Front Hum Neurosci Neuroscience We present a complete framework for time-frequency parametrization of EEG transients, based upon matching pursuit (MP) decomposition, applied to the detection of sleep spindles. Ranges of spindles duration (>0.5 s) and frequency (11–16 Hz) are taken directly from their standard definitions. Minimal amplitude is computed from the distribution of the root mean square (RMS) amplitude of the signal within the frequency band of sleep spindles. Detection algorithm depends on the choice of just one free parameter, which is a percentile of this distribution. Performance of detection is assessed on the first cohort/second subset of the Montreal Archive of Sleep Studies (MASS-C1/SS2). Cross-validation performed on the 19 available overnight recordings returned the optimal percentile of the RMS distribution close to 97 in most cases, and the following overall performance measures: sensitivity 0.63 ± 0.06, positive predictive value 0.47 ± 0.08, and Matthews coefficient of correlation 0.51 ± 0.04. These concordances are similar to the results achieved on this database by other automatic methods. Proposed detailed parametrization of sleep spindles within a universal framework, encompassing also other EEG transients, opens new possibilities of high resolution investigation of their relations and detailed characteristics. MP decomposition, selection of relevant structures, and simple creation of EEG profiles used previously for assessment of brain activity of patients in disorders of consciousness are implemented in a freely available software package Svarog (Signal Viewer, Analyzer and Recorder On GPL) with user-friendly, mouse-driven interface for review and analysis of EEG. Svarog can be downloaded from http://braintech.pl/svarog. Frontiers Media S.A. 2015-05-08 /pmc/articles/PMC4424848/ /pubmed/26005412 http://dx.doi.org/10.3389/fnhum.2015.00258 Text en Copyright © 2015 Durka, Malinowska, Zieleniewska, O'Reilly, Różański and Żygierewicz. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Durka, Piotr J. Malinowska, Urszula Zieleniewska, Magdalena O'Reilly, Christian Różański, Piotr T. Żygierewicz, Jarosław Spindles in Svarog: framework and software for parametrization of EEG transients |
title | Spindles in Svarog: framework and software for parametrization of EEG transients |
title_full | Spindles in Svarog: framework and software for parametrization of EEG transients |
title_fullStr | Spindles in Svarog: framework and software for parametrization of EEG transients |
title_full_unstemmed | Spindles in Svarog: framework and software for parametrization of EEG transients |
title_short | Spindles in Svarog: framework and software for parametrization of EEG transients |
title_sort | spindles in svarog: framework and software for parametrization of eeg transients |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4424848/ https://www.ncbi.nlm.nih.gov/pubmed/26005412 http://dx.doi.org/10.3389/fnhum.2015.00258 |
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