Implementation of tools for lessening the influence of artifacts in EEG signal analysis

TL;DR

This paper presents code tools designed to reduce ocular artifacts in EEG signals, enhancing the analysis of long-duration EEG recordings without discarding trials.

Contribution

It offers practical implementations of methods for artifact reduction in EEG, focusing on ocular artifacts, with illustrative examples and adaptable code scripts.

Findings

Effective reduction of ocular artifacts demonstrated

Tools facilitate analysis of long EEG recordings

Methods improve signal quality without trial removal

Abstract

This manuscript describes and 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 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.