Comparative Study of Band-Power Extraction Techniques for Motor Imagery Classification

We review different techniques for extracting the power information contained in frequency bands in the context of electroencephalography (EEG) based Brain-Computer Interfaces (BCI). In this domain it is common to apply only one algorithm for extracting the power information. However previous work and our current study confirm that one may indeed expect varying degrees of success by choosing inadequate algorithms for the power extraction. Our results suggest that on average one algorithm seems superior for extracting the power information for Motor Imagery tasks : the application of a Morlet wavelet on the raw EEG signals, with the time-frequency resolution tradeoff selected by cross-validation.

Domaines

Traitement du signal et de l'image [eess.SP] Traitement du signal et de l'image [eess.SP]

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bci_powcomp_final.pdf (154.11 Ko)

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https://inria.hal.science/inria-00609161

Soumis le : lundi 18 juillet 2011-14:08:59

Dernière modification le : lundi 5 juin 2023-16:52:12

Archivage à long terme le : lundi 12 novembre 2012-11:11:28

Dates et versions

inria-00609161 , version 1 (18-07-2011)

Identifiants

HAL Id : inria-00609161 , version 1
DOI : 10.1109/CCMB.2011.5952105

Citer

Nicolas Brodu, Fabien Lotte, Anatole Lécuyer. Comparative Study of Band-Power Extraction Techniques for Motor Imagery Classification. IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (SSCI'2011 CCMB), Apr 2011, Paris, France. pp.1-6, ⟨10.1109/CCMB.2011.5952105⟩. ⟨inria-00609161⟩

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