EEG ocular artifact elimination by extraction of ICA component
Keywords:
Electroencephalography (EEG), artifact, Independent Component Analysis (ICA), EEGLAB, MATLABAbstract
Electroencephalography (EEG) is a method to define the ailments and to classify the activity on specific location by examining the brain signals. An EEG recording generally contains numerous artifacts. Elimination of Artifact is a significant concern while dealing with recordings of EEG. This paper offers an innovative method grounded on Independent Component Analysis (ICA) in EEGLAB toolbox of MATLAB to reject eye movement artifacts for elimination of artifacts from the EEG signals. The signals obtained from eye blinks and movements are of more magnitude than generated brain signals and this is the main cause of artifacts in EEG data. The result shows that the offered method is appropriate for removal of eye movement’s artifacts and ideology of this technique can be extended to any other type of artifacts as well. The method is steady, easy to apply and offers a little computational cost.
References
- Akhtar, Muhammad Tahir, Mitsuhashi, Wataru, & James, Christopher J., “Employing spatially constrained ICA and wavelet denoising, for automatic removal of artifacts from multichannel EEG data”, Signal Processing,2012,vol. 92, no.2, pp.401-416.
- Anshul Khatter,Dipali Bansal,Rashima Mahajan, “Study of Various Automatic EEG Artifact Removal Techniques”,International Journal for Research in Applied Science & Engineering Technology”,2017,Vol5,pp1027-1037.
- Eleni Kroupi, Ashkan Yazdani, Jean-Marc Vesin, Touradj Ebrahimi.: Ocular Artifact Removal from EEG: A comparison of subspace projection and adaptive projection methods, Proceedings of 19 European Signal Processing Conference,(2011)
- P Bhuvaneswari, J. Satheesh Kumar , “Methods used for Identifying EEG Signal Artifacts”, 2012 ,Elsevier.
- Samaneh Valipour, G. R. Kulkarni and A. D. Shaligram, “Study on Performance Metrics for Consideration of Efficiency of the Ocular Artifact Removal Algorithms for EEG Signals” ,2015, Indian Journal of Science and Technology, Vol. 8(30).
- Satheesh Kumar, J., and Bhuvaneswari, P., Analysis of Electroencephalography(EEG) Signal and its categorization –A Study,2012, Elseveir Engineering Procedia
- T. Raduntz, J. Scouten, O. Hochmuth, B. Meffert, “EEG artifact elimination by extraction of ICA-component features using image processing algorithms” Journal of Neuroscience Methods(Elsevier) Vol. 243 (2015),pp. 84–93, http://dx.doi.org/10.1016/j.jneumeth.2015.01.030
- Winkler I, Haufe S, Tangermann M. , “Automatic classification of artifactual ICAcomponents for artifact removal in EEG signals. “Behav Brain Funct 2011,http://dx.doi.org/10.1186/1744-9081-7-30.
Downloads
Published
Issue
Section
License
Copyright (c) IJSRSET
This work is licensed under a Creative Commons Attribution 4.0 International License.