Brain-Computer Interface Based on Motor Imagery: the Most Relevant Sources of Electrical Brain Activity

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F14%3A00398560" target="_blank" >RIV/67985807:_____/14:00398560 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27240/14:86096546 RIV/61989100:27740/14:86096546

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-00930-8_14" target="_blank" >http://dx.doi.org/10.1007/978-3-319-00930-8_14</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-00930-8_14" target="_blank" >10.1007/978-3-319-00930-8_14</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Brain-Computer Interface Based on Motor Imagery: the Most Relevant Sources of Electrical Brain Activity

Popis výsledku v původním jazyce

Examined are sources of brain activity, contributing to EEG patterns which correspond to motor imagery during training to control brain-computer interface (BCI). To identify individual source contribution into EEG recorded during the training, Independent Component Analysis (ICA) was employed. Those independent components, for which the BCI system classification accuracy was at maximum, were treated as relevant to performing the motor imagery tasks. To reveal neurophysiological nature of these components we solved the inverse EEG problem in order to localize the sources of brain activity causing these components to appear in EEG. Individual geometry of brain and its covers provided by anatomical MR images, was taken into account when localizing the sources. Their positions were compared with foci of BOLD activity obtained in fMRI study.

Název v anglickém jazyce

Brain-Computer Interface Based on Motor Imagery: the Most Relevant Sources of Electrical Brain Activity

Popis výsledku anglicky

Examined are sources of brain activity, contributing to EEG patterns which correspond to motor imagery during training to control brain-computer interface (BCI). To identify individual source contribution into EEG recorded during the training, Independent Component Analysis (ICA) was employed. Those independent components, for which the BCI system classification accuracy was at maximum, were treated as relevant to performing the motor imagery tasks. To reveal neurophysiological nature of these components we solved the inverse EEG problem in order to localize the sources of brain activity causing these components to appear in EEG. Individual geometry of brain and its covers provided by anatomical MR images, was taken into account when localizing the sources. Their positions were compared with foci of BOLD activity obtained in fMRI study.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: Centrum excelence IT4Innovations</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

Soft Computing in Industrial Applications

ISBN

978-3-319-00929-2

ISSN

2194-5357

e-ISSN

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Počet stran výsledku

11

Strana od-do

153-163

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Anywhere on Earth

Datum konání akce

10. 12. 2012

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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