Detection of ERP and ERD/ERS patterns in single ECoG channels

Author

Graimann, B. ; Huggins, J.E. ; Levine, S.P. ; Pfurtscheller, G.

Author_Institution

Dept. of Med. Informatics, Graz Univ. of Technol., Austria

fYear

2003

fDate

20-22 March 2003

Firstpage

614

Lastpage

617

Abstract

Wavelet packet analysis and a genetic algorithm were used to detect movement-related patterns in single channel electrocorticogram (ECoG). Detection accuracies of more than 90% hits and less than 10% false positives were found. The findings show that the detection of movement-related patterns in ECoG data can be used to reliably provide switch control directly by the brain and is therefore very suitable as the basis of a direct brain interface.

Keywords

genetic algorithms; medical signal processing; signal detection; user interfaces; wavelet transforms; BCI; ECoG data; ERD/ERS patterns; ERP detection; brain computer interface; detection accuracies; direct brain interface; event-related desynchronization; genetic algorithm; movement-related patterns; single ECoG channels; single channel electrocorticogram; switch control; wavelet packet analysis; Algorithm design and analysis; Biomedical engineering; Biomedical informatics; Brain computer interfaces; Enterprise resource planning; Genetic algorithms; Pattern analysis; Switches; Wavelet analysis; Wavelet packets;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Engineering, 2003. Conference Proceedings. First International IEEE EMBS Conference on

Print_ISBN

0-7803-7579-3

Type

conf

DOI

10.1109/CNE.2003.1196903

Filename

1196903