NDLI: Quantitative evaluation of automatic ocular removal from simulated EEG signals: regression vs. second order statistics methods

Content Provider	IEEE Xplore Digital Library
Author	Romero, S. Mananas, M.A. Barbanoj, M.J.
Copyright Year	2006
Description	Author affiliation: Autom. Control Dept., Tech. Univ. of Catalonia, Barcelona (Romero, S.; Mananas, M.A.)
Abstract	Analysis of the EEG by means of spectral parameters permit to evaluate the influence of a drug and to diagnose dysfunctional states in neurology, psychiatry and psychopharmacology. Eye movement artifacts contaminate EEG signals and can produce errors in this analysis. Regression based technique is considered the 'gold standard' artifact removal procedure and other techniques have been developed the last years, but few works have shown an objectively evaluation of the efficiency of these methods because it is impossible to record pure EEG and EOG signals. In this study, an artificially reproduction of bidirectional contaminated EEG and EOG data is proposed in order to simulate a real case. A comparative study between automatic second-order statistics techniques (PCA, AMUSE and SOBI) and multiple regression analysis is performed. Effectiveness of removal techniques is evaluated by calculating the errors in spectral parameters between sources and corrected EEG signals. Average values and topographic brain distribution of these errors are considered. Errors are located in the anterior leads especially in the frontopolar ones. Results show that AMUSE and SOBI methods preserve more cerebral activity than other techniques. We conclude that AMUSE and SOBI algorithms overcome the limitations of the regression based approach in the bidirectional contamination between ocular and neural activity
Sponsorship	IEEE EMB
Starting Page	5495
Ending Page	5498
File Size	435227
Page Count	4
File Format	PDF
ISBN	1424400325
ISSN	1557170X
DOI	10.1109/IEMBS.2006.260338
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Brain modeling Electroencephalography Statistics Electrooculography Drugs Nervous system Psychiatry Psychology Error analysis Signal analysis
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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