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The third was artifact rejection, implemented by rejecting trials that had a range of more than 150 μV.
Partial artifact rejection was performed by rejecting segments of the trials containing eye-blinks, muscle and SQUID artifacts.
Trials retained after the artifact rejection process were used in our averaged ERP analysis.
For the artifact rejection, firstly, apparent eye contaminations in EEG signals were manually removed by visual inspection.
In this paper a new highly accurate artifact rejection method is introduced, called Filter-Bank Artifact Rejection (FBAR), which is designed for real-time EEG applications using just a few or even a single EEG channel.
FBAR is compared to a current state-of-the-art method, Fully Automated Statistical Thresholding for EEG artifact Rejection (FASTER).
Special emphasis will be given to common issues such as choice of reference electrode, filtering, artifact rejection, and spectral analysis.
The same artifact rejection method was used.
For artifact rejection, a simple threshold method was used.
Bipolar vertical and horizontal electrooculograms (EOGs) were recorded for artifact rejection purposes.
Artifact rejection excluded 5.7% of all trials (ranging from 0.19% to 25.6% per participant, SD = 6.4).
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