Real-Time Removal of Ocular Artifacts from EEG Signals Using ICA and Manifold Algorithm
Pei Wang · Xi'an Jiaotong Daxue xuebao · 2010
Aiming at the problem that frequent occurrences of ocular artifacts seriously interfere with the electroencephalogram(EEG) interpretation and analysis,a novel technique to eliminate ocular artifacts from EEG signals in real-time is proposed.The independent component analysis(ICA) is employed to decompose EEG signals,and these independent components features of topography and power spectral density are extracted.Specifically,a template-based isometric mapping(Isomap) algorithm is adopted to reduce the feature dimensionality.The low-dimensional feature samples are fed to a classifier to identify ocular artifacts components.The classification performances of several typical classifiers show that the template-based Isomap algorithm with the nearest neighbor classifier performs best.The experimental results demonstrate the efficiency for removing ocular artifacts with little distortion of underlying brain signals.