REMOVING OCULAR ARTIFACTS FROM EEG RECORDING USING AN ADAPTIVE FILTERIING AND WAVELET TRANSFORM

Abstract

Eye blinks and movements of the eyeballs produce electrical signals that are collectively known as Ocular Artifacts (OA) and these are 10-100 times stronger than EEG signal which is being recorded. Removing artifacts from EEG signal may aid the work of doctors, because artifacts disturb their attention. This research presents a new method to remove automatically ocular artifacts in contaminated EEG signals. The method is based on Recursive Least Square (RLS) Adaptive Filter through stationary wavelet transform (SWT). The stationary wavelet transform (SWT) is used as a pre-stage before the Recursive Least Square (RLS) Adaptive Filtering, to produce ocular artifact free EEG signal. The results show that, in some cases, the method is 20 times better when compared to the use of the traditional FFT method of removing ocular artifacts