Implementation of Tools for Lessening the Influence of Artifacts in EEG Signal Analysis.
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Abstract
This manuscript describes an implementation of scripts of code aimed at reducing the
influence of artifacts, specifically focused on ocular artifacts, in the measurement and processing of
electroencephalogram (EEG) signals. This process is of importance because it benefits the analysis
and study of long trial samples when the appearance of ocular artifacts cannot be avoided by simply
discarding trials. The implementations provided to the reader illustrate, with slight modifications,
previously proposed methods aimed at the partial or complete elimination of EEG channels or
components obtained after independent component analysis (ICA) of EEG signals. These channels
or components are those that resemble the electro-oculogram (EOG) signals in which artifacts are
detected. In addition to the description of each of the provided functions, examples of utilization and
illustrative figures will be included to show the expected results and processing pipeline.
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