Online motor-imagery based BCI

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00194635" target="_blank" >RIV/68407700:21230/12:00194635 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Online motor-imagery based BCI

Popis výsledku v původním jazyce

This contribution presents a study on feedback training using a motor-imagery based brain- computer interface (BCI). In contrast to majority of BCI papers focusing on development of complex signal processing methods, we used the simplest possible available methods to focus on influence of the feedback itself and development of methodology how to conduct the experiments to support user training. We have shown that simple signal processing methods are not only sufficient to achieve high-speed control buttheir usage is desired in online applications as the simple methods can be more easily adapted. We have introduced a novel adaptive threshold classification approach. Classification scores up to 100 % (75 % in average over all subjects and sessions) wereachieved with classification of left and right arm motor imagery and visual feedback in experiments performed in synchronous manner and asynchronous self-paced operation was reached with few proficient subjects.

Název v anglickém jazyce

Online motor-imagery based BCI

Popis výsledku anglicky

This contribution presents a study on feedback training using a motor-imagery based brain- computer interface (BCI). In contrast to majority of BCI papers focusing on development of complex signal processing methods, we used the simplest possible available methods to focus on influence of the feedback itself and development of methodology how to conduct the experiments to support user training. We have shown that simple signal processing methods are not only sufficient to achieve high-speed control buttheir usage is desired in online applications as the simple methods can be more easily adapted. We have introduced a novel adaptive threshold classification approach. Classification scores up to 100 % (75 % in average over all subjects and sessions) wereachieved with classification of left and right arm motor imagery and visual feedback in experiments performed in synchronous manner and asynchronous self-paced operation was reached with few proficient subjects.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GAP102%2F11%2F1795" target="_blank" >GAP102/11/1795: Nové selektivní transformace pro číslicové zpracování nestacionárních signálů</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název statě ve sborníku

2012 International Conference on Applied Electronics

ISBN

978-80-261-0038-6

ISSN

1803-7232

e-ISSN

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Počet stran výsledku

4

Strana od-do

65-68

Název nakladatele

University of West Bohemia

Místo vydání

Pilsen

Místo konání akce

Plzeň

Datum konání akce

6. 9. 2012

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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