Discrimination of electroencephalogram considering spatial arrangement of electrodes

Abstract

In this study, we have designed appropriate combination of pre-processing and classifiers to identify human thought contents from measured brain waves. Analysis data include 5 subjects of data set 1 of BCI Competition IV. Subject recalls left and right hand movements. The differences at that time were identified by two classifications by CNN. An electrode layout was set in consideration of the spatial proximity of the electrodes of electroencephalogram measurement. The number of time divisions of the measured data was set as the number of channels of CNN. After that, the subject's movements were identified from the brain wave data given the spatial structure. As a result, the discrimination rate was 58.8%.