A global approach for automatic artifact removal for standard EEG record

Abstract

The EEG signal is a record of the brain activity using multiple electrodes placed on the scalp. Unfortunately, it can be hardly contaminated by a lot of noises called artifacts. These latter can be generated by various actions such as eye blinks, eye movements or the skeletal muscle activities (jaw, forehead, ...). This study will focus on a global artifact removal method using independent component analysis (ICA) on signals cut in frequency bands. The interest of this method resides in automatizing the artifactual source identification and enables a global filtering of records using constant bases. A brief overview of the project will be made in order to introduce the method used. Next, the results will be presented and their validation will be discussed in the conclusion.