Classification of the EEG feature components

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Classification of the EEG feature components

Popis výsledku v původním jazyce

In this paper we propose a novel method for the EEG signal processing based on the classification of independent components of the signal features. ICA algorithm has been successfully applied to the area of EEG artefact detection, however this algorithmcan be applied to identify independent components of signal features. We decomposed the EEG signal to the descriptive features, calculated independent components for specific features, linked them to the appropriate electrodes and classified these feature components by several algorithms. This method was applied to the data from a psychological experiment focused on the adoption of a specific frame of reference within the spatial navigation. The results were compared with the widely adopted method of signal feature classification. The feature components method revealed the brain structures involved in the spatial navigation similar to the results of recent EEG and fMRI studies.

Název v anglickém jazyce

Classification of the EEG feature components

Popis výsledku anglicky

In this paper we propose a novel method for the EEG signal processing based on the classification of independent components of the signal features. ICA algorithm has been successfully applied to the area of EEG artefact detection, however this algorithmcan be applied to identify independent components of signal features. We decomposed the EEG signal to the descriptive features, calculated independent components for specific features, linked them to the appropriate electrodes and classified these feature components by several algorithms. This method was applied to the data from a psychological experiment focused on the adoption of a specific frame of reference within the spatial navigation. The results were compared with the widely adopted method of signal feature classification. The feature components method revealed the brain structures involved in the spatial navigation similar to the results of recent EEG and fMRI studies.

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2010

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

10th International Conference on Information Technology and Applications in Biomedicine

ISBN

978-1-4244-6560-6

ISSN

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e-ISSN

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Počet stran výsledku

1

Strana od-do

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Název nakladatele

IEEE Control Syst Soc

Místo vydání

Crete

Místo konání akce

Aquis Corfu Holiday Palace Hotel

Datum konání akce

3. 11. 2010

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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