Correction of Ocular Artifacts in the EEG Using Bayesian Adaptive Regression Splines

Ocular activity is a significant source of artifacts in the electroencephalogram (EEG). Regression upon the electrooculogram (EOG) is commonly used to correct the EEG. It is known, however, that this approach also removes high-frequency cerebral activity from the EEG. To counter this effect, we used Bayesian Adaptive Regression Splines (BARS) (DiMatteo (2001); DiMatteo, Genovese, and Kass (2001)) to adaptively filter the EOG of high-frequency activity before using the EOG for correction. In a preliminary simulation study, this approach reduced spectral error rates in higher frequency bands.

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