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On the methodological unification in electroencephalography
BACKGROUND: This paper presents results of a pursuit of a repeatable and objective methodology of analysis of the electroencephalographic (EEG) time series. METHODS: Adaptive time-frequency approximations of EEG are discussed in the light of the available experimental and theoretical evidence, and a...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2005
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1160515/ https://www.ncbi.nlm.nih.gov/pubmed/15748284 http://dx.doi.org/10.1186/1475-925X-4-15 |
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author | Durka, Piotr J |
author_facet | Durka, Piotr J |
author_sort | Durka, Piotr J |
collection | PubMed |
description | BACKGROUND: This paper presents results of a pursuit of a repeatable and objective methodology of analysis of the electroencephalographic (EEG) time series. METHODS: Adaptive time-frequency approximations of EEG are discussed in the light of the available experimental and theoretical evidence, and applicability in various experimental and clinical setups. RESULTS: Four lemmas and three conjectures support the following conclusion. CONCLUSION: Adaptive time-frequency approximations of signals unify most of the univariate computational approaches to EEG analysis, and offer compatibility with its traditional (visual) analysis, used in clinical applications. |
format | Text |
id | pubmed-1160515 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-11605152005-06-28 On the methodological unification in electroencephalography Durka, Piotr J Biomed Eng Online Review BACKGROUND: This paper presents results of a pursuit of a repeatable and objective methodology of analysis of the electroencephalographic (EEG) time series. METHODS: Adaptive time-frequency approximations of EEG are discussed in the light of the available experimental and theoretical evidence, and applicability in various experimental and clinical setups. RESULTS: Four lemmas and three conjectures support the following conclusion. CONCLUSION: Adaptive time-frequency approximations of signals unify most of the univariate computational approaches to EEG analysis, and offer compatibility with its traditional (visual) analysis, used in clinical applications. BioMed Central 2005-03-04 /pmc/articles/PMC1160515/ /pubmed/15748284 http://dx.doi.org/10.1186/1475-925X-4-15 Text en Copyright © 2005 Durka; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Durka, Piotr J On the methodological unification in electroencephalography |
title | On the methodological unification in electroencephalography |
title_full | On the methodological unification in electroencephalography |
title_fullStr | On the methodological unification in electroencephalography |
title_full_unstemmed | On the methodological unification in electroencephalography |
title_short | On the methodological unification in electroencephalography |
title_sort | on the methodological unification in electroencephalography |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1160515/ https://www.ncbi.nlm.nih.gov/pubmed/15748284 http://dx.doi.org/10.1186/1475-925X-4-15 |
work_keys_str_mv | AT durkapiotrj onthemethodologicalunificationinelectroencephalography |