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Abstract:
We have studied the application of an independent component
analysis (ICA) approach to the identification and possible removal
of artifacts from a magnetoencephalographic (MEG) recording. This
statistical technique separates components according to the
kurtosis of their amplitude distributions over time, thus
distinguishing between strictly periodical signals, and regularly
and irregularly occurring signals. Many artifacts belong to the
last category. In order to assess the effectiveness of the method,
controlled artifacts were produced, which included saccadic eye
movements and blinks, increased muscular tension due to biting and
the presence of a digital watch inside the magnetically shielded
room. The results demonstrate the capability of the method to
identify and clearly isolate the produced artifacts.
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