Prediction of individual finger movements for motor execution and imagery: An EEG study

In the study of brain computer interface using electroencephalogram (EEG), the area of motor imagery of individual finger movement has been extensively examined. The objective of this study is to predict which finger is moving or being imaged through the use of EEG. We measured EEG activity while subjects performed either motor execution or motor imagery of individual finger movements with their right hand. Event related spectral perturbation was used as indicator of brain activity, which represents frequency power fluctuation from the baseline interval. The frequency bands α, β, and γ (8-15, 16-31, and 32-128 Hz, respectively) were used for analysis. Additionally, a feature consisting of a combination of those three bands was also explored using principal component analysis. These four kinds of features were classified by a linear discriminant analysis using ten-fold cross validation. Result indicated that the combined feature of the three frequency bands could classify most combinations of finger in both motor execution and motor imagery. The results suggest that EEG during the performance of motor imagery of individual finger movement is discriminable depending on the subject.