BCI Competition 2003—Data Set Ia: Combining Gamma-Band Power With Slow Cortical Potentials to Improve Single-Trial Classification of Electroencephalographic Signals

B.D. Mensh, J. Werfel, H.S. Seung
2004 IEEE Transactions on Biomedical Engineering  
In one type of brain-computer interface (BCI), users self-modulate brain activity as detected by electroencephalography (EEG). To infer user intent, EEG signals are classified by algorithms which typically use only one of the several types of information available in these signals. One such BCI uses slow cortical potential (SCP) measures to classify single trials. We complemented these measures with estimates of high-frequency (gamma-band) activity, which has been associated with attentional
more » ... intentional states. Using a simple linear classifier, we obtained significantly greater classification accuracy using both types of information from the same recording epochs compared to using SCPs alone.
doi:10.1109/tbme.2004.827081 pmid:15188877 fatcat:tas5zb4rjrdh7cefovvndkuvvi