NDLI: EEG feature extraction and pattern recognition during right and left hands motor imagery in brain-computer interface

Content Provider	IEEE Xplore Digital Library
Author	Cheng Liu Hailing Wang Hui Pu Yi Zhang Ling Zou
Copyright Year	2012
Description	Author affiliation: Sch. of Inf. Sci. & Eng., Changzhou Univ., Changzhou, China (Cheng Liu; Hailing Wang; Hui Pu; Yi Zhang; Ling Zou)
Abstract	At present, it is an important issue to obtain accurate classification of EEG signal in brain-computer interface. We collected the EEG data which are recorded at a sampling rate of 250Hz by EGI-64 scalp electrodes placed according to the international 10/20 system. Firstly, discrete wavelet transform method is used to decompose the average power of the channel C3/C4 and P3/P4 in left and right hands imagine movement during the some experimental period of time. The reconstructed signal of approximation coefficient A6 on the sixth level is selected to build up a feature signal. Secondly, the performances by Fisher Linear Discriminant Analysis and Support Vector Machine methods are compared. The final classifications results show that correct classification rate by Support Vector Machine is higher and gain an ideal classification results, which can establish a basis of real-time BCI application.
Starting Page	506
Ending Page	510
File Size	512184
Page Count	5
File Format	PDF
ISBN	9781467311830
e-ISBN	9781467311847
DOI	10.1109/BMEI.2012.6513023
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Pattern Classification Motor Imagery Feature Extraction Brain-Computer Interface
Content Type	Text
Resource Type	Article

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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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