Automatic removal of EOG artifacts using SOBI algorithm combined with intelligent source identification technique

Abstract

Electrooculography (EOG) artifacts, generated by winking or other eye's movements, should be eliminated because they are the cause of the wrong decision in analysis the Electroencephalography (EEG) data, especially in the diagnosis of epilepsy. One of the efficient methods for signal separation is the Second order blind identification (SOBI), a blind source separation technique. In most cases, the activities of the two eyes are the same, and SOBI identify that there is only one source of artifact. However, in some cases, the activities of the two eyes are different, and SOBI identify that there are two different sources of artifacts [1]. The problem is that SOBI cannot provide the information about the order of sources. It means that, it cannot point out how many sources of EOG. It would lead to the wrong decision in EEG analysis. To solve this current limitation, in this paper, we propose an effective method to remove EOG from EEG using SOBI combined with intelligent source identification technique. The proposed method was evaluated carefully using experimental data. It determined successfully the number of EOG sources and removes these artifacts more accurately and efficiently.