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The purpose of this paper is to investigate the applicability of duty cycle for steady-state visual evoked potential (SSVEP)-based application. For this, the time-frequency analysis of SSVEP during visual stimuli presentation with different duty cycles was performed. The commercial wireless EEG headset with O1 and O2 channels was utilized to record the associated brain activity. The experimental paradigm,...
An automatic artifact removal method of magnetoencephalogram (MEG) was presented in this paper. The method proposed is based on independent components analysis (ICA) and support vector machine (SVM). However, different from the previous studies, in this paper we consider two factors which would influence the performance. First, the imbalance factor of independent components (ICs) of MEG is handled...
This paper presents an automatic method to remove physiological artifacts from magnetoencephalogram (MEG) data based on independent component analysis (ICA). The proposed features including kurtosis (K), probability density (PD), central moment of frequency (CMoF), spectral entropy (SpecEn), and fractal dimension (FD) were used to identify the artifactual components such as cardiac, ocular, muscular,...
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