Various artifacts reduction algorithms for EEG recorded in continuous fMRI scan environment

The EEG recorded in fMRI scanner are totally submerged in gradient, ballistocardiogram and ocular artifacts. Traditional ways to reduce these artifacts have many limitations. AAS has a high requirement on recording and calculating and ICA denoising can be hardly done objectively without extra references. In this paper, we try to simplify and improve the AAS to lower its requirements on calculating. PCA dimension reduction is also introduced to overcome the problem of ICA denoising. A various artifacts removal method is developed based on improved AAS called Re-seg AAS and ICA&PCA. Comparisons before and after each processing step in both time and frequency domain shows that proposed method reduce gradient, ballistocardiogram and ocular artifacts effectively.