Frequency component selection for an ECoG-based brain-computer interface
Scherer, R.; Graimann, B.; Huggins, J.E.; Levine, S.P.; Pfurtscheller, G.
Biomedizinische Technik. Biomedical Engineering 48(1-2): 31-36
2003
ISSN/ISBN: 0013-5585 PMID: 12655847 Document Number: 556467
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.