NDLI: Benefits of ICA in the Case of a Few Channel EEG

Content Provider	IEEE Xplore Digital Library
Author	Rejer, I. Gorski, P.
Copyright Year	2015
Description	Author affiliation: Fac. of Comput. Sci., West Pomeranian Univ. of Technol., Szczecin, Poland (Rejer, I.; Gorski, P.)
Abstract	Independent Component Analysis (ICA) is often used at the signal preprocessing stage in EEG analysis for its ability to filter out artifacts from the signal. The benefits of using ICA are the most apparent when multi-channel signal is recorded. The question is, however, what kind of benefits (if any) can be obtained when ICA is applied for a few channel recording. We addressed this question in this paper by setting up the hypothesis that even in the case of only three channels, ICA can rearrange the sources to new mixtures in such a way that the true brain sources will be enhanced in some components, and the artifacts will be enhanced in others. To verify our hypothesis we applied three popular ICA algorithms to preprocess data from a benchmark file (motor imagery file from the II BCI Competition). Our results, presented in terms of classification precision, show that all ICA algorithms enhanced the signal to noise ratio for components correlating with signals recorded over C3 and C4 channels (the classification precision was higher in their case) and lessened the signal to noise ratio for components correlating with signals recorded over Cz channels.
Starting Page	7434
Ending Page	7437
File Size	637223
Page Count	4
File Format	PDF
ISSN	1557170X
e-ISBN	9781424492718
DOI	10.1109/EMBC.2015.7320110
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-25
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Classification algorithms Correlation Accuracy Independent component analysis Algorithm design and analysis Signal to noise ratio
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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