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PubMed · 12655847

Frequency component selection for an ECoG-based brain-computer interface.

R Scherer·B Graimann·J E Huggins·S P Levine·G Pfurtscheller
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Abstract

The aim of the present study was to investigate the most significant frequency components in electrocorticogram (ECoG) recordings in order to operate a brain computer interface (BCI). For this purpose the time-frequency ERD/ERS map and the distinction sensitive learning vector quantization (DSLVQ) are applied to ECoG from three subjects, recorded during a self-paced finger movement. The results show that the ERD/ERS pattern found in ECoG generally matches the ERD/ERS pattern found in EEG recordings, but has an increased prevalence of frequency components in the beta range.

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Brain MappingCerebral CortexCortical SynchronizationElectroencephalographyElectromyographyEpilepsyEvoked PotentialsHumansMotor ActivityNerve NetSignal Processing, Computer-AssistedUser-Computer InterfaceJournal ArticleResearch Support, U.S. Gov't, P.H.S.

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R Scherer, B Graimann, J E Huggins, S P Levine, G Pfurtscheller. Frequency component selection for an ECoG-based brain-computer interface.. https://doi.org/10.1515/bmte.2003.48.1-2.31

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