The removal of blink and saccade artifact in EEG recordings by Independent Component Analysis

Pervasive electroencephalographic (EEG) artifacts are associated with eye movement. This study shows that Independent Component Analysis (ICA) using Joint Approximate Diagonalization of Eigenmatrice (JADE) algorithm can be applied to removing ocular artifacts in EEG. The nine channels of EEGs were recorded from three young healthy subjects with additional VEOG and HEOG channels in blinking and saccade conditions respectively. Seven EEG recordings were selected for artifacts removal tests with two EOG recordings indicating the possible interferences. Ocular artifacts for both conditions were successfully presented by an independent component, which was then eliminated to reconstruct the artifact-free EEGs. This study demonstrates that JADE algorithm can be an effective tool in correcting EOG interference with multichannel EEG recordings.