Online artifact removal in EEG signals

Abstract

A Brain Computer Interface(BCI) is a communication tool between human and external devices by means of electroencephalogram(EEG) which is the recording of electrical activity derived from scalp. EEG contains some artifacts because of body movement and eye blinking, for example. Therefore subjects must not to move and blink during experiment to get fine data. EEG signal with artifact is eliminated in the offline analysis. However, in the online BCI system, artifacts must be removed to avoid malfunction. Independent component analysis (ICA) has become one of the most prominent techniques for EEG. In generally, method of using ICA can remove artifacts after the offline training, but such a method is not suitable for BCI systems in the online driving. In this study, we propose a method the online EOG artifact removal method using ICA, and verify the effect of this method in the δ(1-3Hz), θ(4-7Hz), α(8-12Hz), β(14-30Hz) frequency range. Eye blinks components detection is based on kurtosis. First, the occurrence of a blink is detected by observing the EEG. Next, set the interval that contains the blink and apply ICA to EEG in the interval. Blink components obtained by ICA is determined by the kurtosis. After that, blink artifact components are removed. The EEG has been rebuilt using the other independent components obtained by ICA. As a result, it can remove the effect of EOG artifact in all frequency range.