Certain Analysis on Eeg for the Detection of Eog Artifact Using Symlet Wavelet

This paper presents a statistical method for identification of ocular artifacts in the electroencephalogram (EEG) records. The occurrence of artifacts in EEG signals is due to various factors, like power line interference, EOG (electrooculogram) and ECG (electrocardiogram). The identification of ocular artifact from scalp EEGs is mandatory for both the automated and visual analysis of underlying brainwave activity. These noise sources increase the difficulty in analyzing the EEG and obtaining clinical information. For this reason, it is necessary to design a procedure to decrease such artifacts in EEG records. Here for identification of ocular artifacts, the Stationary Wavelet Transform (SWT) with symlet as a basis function is used and without using the reference of EOG channel the artifacts has been identified. Using this statistical approach, the artifact ocular zones are very easily identified.