EEG classification of physiological conditions in 2D/3D environments using neural network

Higher classification accuracy is more desirable for brain computer interface (BCI) applications. The accuracy can be achieved by appropriate selection of relevant features. In this paper a new scheme is proposed based on six different nonlinear features. These features include Sample entropy (SampE...

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Bibliographic Details
Main Authors: Mumtaz, Wajid, Xia, Likun, Malik, Aamir Saeed, Mohd Yasin, Mohd Azhar
Format: Conference or Workshop Item
Published: 2013
Subjects:
Online Access:http://eprints.utp.edu.my/10826/1/EEG%20Classification%20of%20Physiological%20Conditions%20in%202D_3D.pdf
http://dx.doi.org/10.1109/EMBC.2013.6610480
http://eprints.utp.edu.my/10826/
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Institution: Universiti Teknologi Petronas