NDLI: Classification of Motor Imagery EEG Signals Based on Energy Entropy

Content Provider	IEEE Xplore Digital Library
Author	Dan Xiao Zhengdong Mu Jianfeng Hu
Copyright Year	2009
Abstract	Feature extraction and classification of EEG signals is core issues on EEG-based brain computer interface (BCI). Typically, such classification has been performed using signals from a set of selected EEG sensors. Because EEG sensor signals are mixtures of effective signals and noise, which has low signal-to-noise ratio, motor imagery EEG signals can be difficult to classification. Energy entropy was used to preprocess motor imagery EEG data, and the Fisher class separability criterion was used to extract features. Finally, classification of four types motor imagery EEG was performed by a method based on the statistical theory. An average of 85% classification accuracy of the six type combination and the three subjects was achieved. The results showed that motor imagery EEG signals can be extracted using energy entropy and that these extracted features offered clear advantages for classification.
Starting Page	61
Ending Page	64
File Size	448523
Page Count	4
File Format	PDF
ISBN	9780769536194
DOI	10.1109/IUCE.2009.57
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer interfaces Tongue EEG Electroencephalography Entropy Brain computer interface Timefrequency analysis Foot Electrodes Energy entropy Feature extraction Signal analysis Brain computer interfaces Signal to noise ratio
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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