International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 168 - Issue 4 |
Published: Jun 2017 |
Authors: Alaa Eldeen M. Helal, Ahmed Farag Seddik, Ayat Allah F. Hussein |
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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 }, year = { 2017 }, volume = { 168 }, number = { 4 }, pages = { 10-19 }, doi = { 10.5120/ijca2017914301 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2017 %A Alaa Eldeen M. Helal %A Ahmed Farag Seddik %A Ayat Allah F. Hussein %T A Hybrid Approach for Artifacts Removal from EEG Recordings%T %J International Journal of Computer Applications %V 168 %N 4 %P 10-19 %R 10.5120/ijca2017914301 %I Foundation of Computer Science (FCS), NY, USA
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.