NDLI: Optimal mental task discrimination for brain-computer interface

Content Provider	IEEE Xplore Digital Library
Author	Salerno, M. Costantini, G. Casali, D. Saggio, G. Bianchi, L.
Copyright Year	2010
Description	Author affiliation: Dipartimento di Neuroscienze, Università di Roma ¿Tor Vergata¿, Rome, Italy (Bianchi, L.) \|\| Dipartimento di Ingegneria Elettronica, Università di Roma ¿Tor Vergata¿, Rome, Italy (Salerno, M.; Costantini, G.; Casali, D.; Saggio, G.)
Abstract	A Support Vector Machine (SVM) classification method for data acquired by EEG recording for brain/computer interface systems is here proposed. The aim of this work is to evaluate the SVM performance in the recognition of a human mental task, among others. A prerequisite has been the developing of a system able to recognize and classify the following four tasks: thinking to move the right hand, thinking to move the left hand, performing a simple mathematical operation, and thinking to a nursery rhyme. The data set exploited in the training and testing phases has been acquired by means of 61 EEG electrodes and consists of 4000 time series. These time data sets were then transformed into the frequency domain, in order to obtain the power frequency spectrum. In such a way, for every electrode, 128 frequency channels were obtained. Finally, the SVM algorithm was used and evaluated to get the proposed classification. Different choices of electrodes have been considered: we found that analysing only a subset of electrodes we can get better results than considering all the 63 electrodes.
Starting Page	1346
Ending Page	1349
File Size	299382
Page Count	4
File Format	PDF
ISBN	9781424457939
e-ISBN	9781424457953
DOI	10.1109/MELCON.2010.5475987
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-04-26
Publisher Place	Malta
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Brain computer interfaces Electrodes Support vector machines Support vector machine classification Electroencephalography Artificial neural networks Testing Sensor systems Frequency domain analysis Scalp
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
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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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