Electrodes connection on the scalp needs to apply gel or paste on the scalp and fit EEG-cap on the head and this procedure also needs to deal with the hair on it. By comparison, to fit EEG electrodes on the forehead area is much easier because there is no hair on it. If correlations of the EEGs generated from the forehead area are high with respect to EEGs from the sensorimotor area, it is then possible to achieve relatively high classification accuracy in motor imagery tasks just using EEG from forehead channels. In this way, it will help to make the procedure of motor imagery tasks much easier and convenient. Because correlation coefficients is often used to measure the similarity of two signals, it is necessary to study whether there is a high correlation between forehead channels' EEG and EEG from sensorimotor area during MI(Motor Imagery) tasks. In this paper, EEG data from three subjects were used in the tests. Firstly, a test was conducted on the correlation between EEGs from forehead 8(Fp1-Af8) channels and EEGs from the sensorimotor area channel C3, C4 during the MI tasks. The correlation is calculated with respect to ERP (Event-Related-Potential), Spectral Power between 6-25Hz, and ERSP (Event-Related-Spectral-Perturbation) at Alpha rhythms 8-12Hz. The results of the correlation tests are mostly above 70%. In particular, for subject Sl1, the correlation coefficient of ERSP between forehead channels and C3, C4 are as high as 0.9 during the left hand movement imagery trials. Secondly, we did a test on the classification of imagined left/right hand movement tasks using EEGs from 8 electrodes in the forehead. Classification results show that the accuracy of the forehead 8 channels' EEGs are as high as 81% for subject Sk6 comparing to 90% using 29 channels' EEG signal neighboring to C3, C4. For subject Sk3 and subject Sl1, the accuracies are 65% and 79% comparing to 80% and 83% using EEG signals from 29 channels neighboring to C3, C4. So there are high correlation between EEGs from the forehead area and EEGs from the sensorimotor area. That is to say, we can use EEGs from forehead in some situations, such as classification of left/right imagery, because they are much easier to measure than EEG form the sensorimotor area. This will make BCI system more portable and more convenient to use.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.