NDLI: Developing a few-channel hybrid BCI system by using motor imagery with SSVEP assist

Content Provider	IEEE Xplore Digital Library
Author	Li-Wei Ko Shih-Chuan Lin Meng-Shue Song Komarov, O.
Copyright Year	2014
Description	Author affiliation: Dept. of Biol. Sci. & Technol., Nat. Chiao Tung Univ., Hsinchu, Taiwan (Li-Wei Ko; Shih-Chuan Lin; Meng-Shue Song; Komarov, O.)
Abstract	Generally, Steady-State Visually Evoked Potentials (SSVEP) has widely recognized advantages, like being easy to use, requiring little user training [1], while Motor Imagery (MI) is not easy to introduce for some subjects. This work introduces a hybrid brain-computer interface (BCI) combines MI and SSVEP strategies - such an approach allows us to improve performance and universality of the system, and also the number of EEG electrodes from 32 to 3 in central area can increase the efficiency of EEG preprocessing to design an effective and easy way to use hybrid BCI system. In this study the Common Spatial Pattern (CSP) algorithm was introduced as a feature extraction method, which provides a high accuracy in event-related synchronization/desynchronization (ERS/ERD)-based BCL The four most common classifiers (KNNC, PARZENDC, LDC, SVC) were used for accuracy estimation. Results show that support vector classifier (SVC) and K-nearest-neighbor (KNN) classifier provide better performance than others, and it is possible to reach the same good accuracy using 3-channel (C3, Cz, C4) hybrid BCI system, as with usual 32-channel system.
Starting Page	4114
Ending Page	4120
File Size	6751409
Page Count	7
File Format	PDF
ISSN	21614407
e-ISBN	9781479914845
DOI	10.1109/IJCNN.2014.6889901
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Accuracy Feature extraction Eigenvalues and eigenfunctions Static VAr compensators Time-frequency analysis Covariance matrices electroencephalogram (EEG) channel reduction hybrid brain computer interface (BCI) Motor Imagery (MI) Steady State Visually Evoked Potentials (SSVEP)
Content Type	Text
Resource Type	Article

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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