An effective procedure for reducing EOG and EMG artefacts from EEG signals

Epilepsy is a neural disorder in which the electrical discharge in the brain is abnormal, synchronized and excessive. Scalp Electroencephalogram (EEG) is often used in the diagnosis and treatment of epilepsy by examining the epileptic seizures and epileptic spikes. By modeling the signal acquired at each electrode of the EEG measurement system as a linear combination of source signals generated in the brain, we can apply Blind Source Separation (BSS) techniques to separate the brain activity from other activities. In this paper, we concentrate on applying Second-Order Blind Identification (SOBI) algorithm to remove eye (EOG) and muscular (EMG) artifacts. However, the disadvantage of SOBI is that it cannot provide the information about the order of sources, thus, an identification procedures of artifacts is further needed. The effectiveness of this method has been examined and verified by simulated and experiment data.