EYEBLINK ARTEFACT REMOVAL FROM EEG USING INDEPENDENT COMPONENT ANALYSIS

Abstract

The electrical activity of the human brain is recorded using Electroencephalogram (EEG).Most Often, an EEG signal is contaminated with some unwanted signals called artefact.Artefacts are due to eyeblink (EB), eyeball movement, sweat, power line and muscle.It is very essential to remove such artifact from an EEG signal without losing integrity.In this project, detection and removal of eyeblink artefact has been carried out.Linear feature has been taken to detect an EB artefact in an EEG signal and it's been validated with Spectrogram.Using independent component analysis (ICA), EB artifacts are removed.This project uses some of the algorithms like Algorithm for multiple unknown source extraction (AMUSE), Second order blind identification (SOBI), Joint approximate diagonalization of Eigen matrices (JADE) and Second order non stationary source separation (SONS) which performs ICA for removal of EB artifact.Correlation coefficient is calculated between an original signals and reconstructed signals which are obtained using the above four algorithms.It is found that SOBI and JADE algorithm performs better when compared to other two algorithms.