Abstract
Saccade-related electroencephalogram (EEG) signals
have been the subject of application oriented research by
our group toward developing a brain computer interface (BCI).
Our goal is to develop novel BCI based on eye movements
system employing EEG signals on-line. Most of the analysis of the
saccade-related EEG data has been performed using ensemble
averaging approaches.
In signal processing method for BCI, raw EEG signals are
analyzed. In ensemble averaging method which is major EEG
analysis is not suitable for processing raw EEG signals.
In order to process raw EEG data, we use independent
component analysis. This paper presents extraction rate of
saccade-related EEG signals by four ICA algorithms and six
window size.
As results of extracting rate focused on ICA algorithm, The
JADE and Fast ICA have good results. As you know, calucuration
time in Fast ICA is fater than calucuration time in JADE.
Therefore, in this case, Fast ICA is best in order to extract
saccade-related ICs.
Next, we focus on extracting rate in each windows. The
windows not including EEG signals after saccade has and the
windows which has small window size is good extracting rate.
