An Application of Gaussian Processes on Ocular Artifact Removal from EEG

Saman Noorzadeh (1, 2) , Bertrand Rivet (1) , Pierre-Yves Guméry (2)

1 GIPSA-VIBS - GIPSA - Vision and Brain Signal Processing
2 TIMC-IMAG-PRETA - Physiologie cardio-Respiratoire Expérimentale Théorique et Appliquée

Consequences of eye movements are one of the main inferences that distort the brain EEG recordings. In this paper, a multi-modal approach is used to estimate the ocular artifacts in the EEG: both vertical and horizontal eye movement signals recoded by an eye tracker are used as a reference to denoise the EEG. A Gaussian process, i.e. a second order statistics method, is assumed to model the link between the eye tracker signals and the EEG signals. The proposed method is thus a non-linear extension of the well-known adaptive filtering and can be applied with a single EEG signal contrary to independent component analysis (ICA) which is extensively used. The results show the applicability and the efficiency of this model on the ocular artifact removal.

Domaines: Traitement du signal et de l'image [eess.SP]

Saman Noorzadeh, Bertrand Rivet, Pierre-Yves Guméry. An Application of Gaussian Processes on Ocular Artifact Removal from EEG. EMBC 2015 - 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Aug 2015, Milan, Italy. ⟨10.1109/EMBC.2015.7318422⟩. ⟨hal-01197114⟩