Preprocessing Pipelines for EEG

¹ Research Scholar Department of Computer Science CHRIST (Deemed to be University)
² Associate Professor Department of Computer Science CHRIST (Deemed to be University)

^a) sherly.maria@res.christuniversity.in
^b) chandra.j@christuniversity.in

Abstract

(Use the Microsoft Word template style: Author Email) or (Use Times New Roman Font: 10 pt, Italic, Centered) Electroencephalogram (EEG) signals collected, present a lot of challenges in order to process the data. Usually, the signals collected contain a lot of artifacts and noises. To address this issue and to make the preprocessing method easier and automated. EEG is widely used to record brain signals and activity for clinical and research purposes. EEG signals are the best way to understand brain signals compared to other methods because of how accurate it is. However, it comes with certain setbacks like being highly sensitive to noise and susceptible to artifacts. Hence developing a pre-processing method ensures a smooth understanding of the signals. These pre-processing methods include filtering and noise removal techniques. Section 1 includes the pre-processing pipelines that have been popularly used by researchers during this study. Section 2 consists of the results and comparisons of various pipelines and our understanding of what is more effective.