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A Hybrid Approach for Artifacts Removal from EEG Recordings

by Alaa Eldeen M. Helal, Ahmed Farag Seddik, Ayat Allah F. Hussein
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 168 - Number 4
Year of Publication: 2017
Authors: Alaa Eldeen M. Helal, Ahmed Farag Seddik, Ayat Allah F. Hussein
10.5120/ijca2017914301

Alaa Eldeen M. Helal, Ahmed Farag Seddik, Ayat Allah F. Hussein . A Hybrid Approach for Artifacts Removal from EEG Recordings. International Journal of Computer Applications. 168, 4 ( Jun 2017), 10-19. DOI=10.5120/ijca2017914301

@article{ 10.5120/ijca2017914301,
author = { Alaa Eldeen M. Helal, Ahmed Farag Seddik, Ayat Allah F. Hussein },
title = { A Hybrid Approach for Artifacts Removal from EEG Recordings },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2017 },
volume = { 168 },
number = { 4 },
month = { Jun },
year = { 2017 },
issn = { 0975-8887 },
pages = { 10-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume168/number4/27861-2017914301/ },
doi = { 10.5120/ijca2017914301 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:15:13.029209+05:30
%A Alaa Eldeen M. Helal
%A Ahmed Farag Seddik
%A Ayat Allah F. Hussein
%T A Hybrid Approach for Artifacts Removal from EEG Recordings
%J International Journal of Computer Applications
%@ 0975-8887
%V 168
%N 4
%P 10-19
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The electroencephalogram (EEG) is a widely used traditional procedure for diagnosing, monitoring and managing neurological disorders. Many artifact types that often contaminate EEG remain a key challenge for precise diagnosis of brain dysfunctions and neurological disorders. Hence, artifact removal is intuitively required for accurate EEG analysis and treatment. This paper presents a new extensive method that can remove a wide variety of EEG artifacts based mainly on Template Matching approach including multiple signal-processing tools. The method was evaluated and validated on real EEG data, giving promising results that offer better capabilities to neurophysiologists in routine EEG examinations and diagnosis.

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Index Terms

Computer Science
Information Sciences

Keywords

Electroencephalogram (EEG) artifacts removal independent component analysis wavelet cosine similarity measure

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