Reference Signal Based Tensor Product Expansion for EOG-Related Artifact Separation in EEG

Akitoshi Itai, Arao Funase, Andrzej Cichocki, Hiroshi Yasukawa

Abstract: This paper describes the background noise estimation technique of the tensor product expansion with absolute error (TPE-AE) to estimate multiple sources. The electroencephalogram (EEG) signal produced by the saccadic eye movement is adopted to analyze relationship between a brain function and a human activity. The electrooculogram (EOG) generated by eye movements yields significant problems for the EEG analysis. The denoising of EOG artifacts is important task to perform an accurate analysis. In this paper, the two types of TPE-AE are proposed to estimates EOG and other components in EEG during eye movement. One technique estimates two outer products using median filter based TPE-AE. The another technique uses a reference signal to separate the two sources. We show that the proposed method is effective to estimate and separate two sources in EEG.