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DOI: 10.14569/IJARAI.2014.031002
PDF

Discrimination of EEG-Based Motor Imagery Tasks by Means of a Simple Phase Information Method

Author 1: Ana Loboda
Author 2: Alexandra Margineanu
Author 3: Gabriela Rotariu
Author 4: Anca Mihaela Lazar

International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 3 Issue 10, 2014.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: We propose an off-line analysis method in order to discriminate between motor imagery tasks manipulated in a brain computer interface system. A measure of large-scale synchronization based on phase locking value is established. The results indicate that it can take advantage of the phase synchrony between scalp-recorded EEG activity in the supplementary motor area and in sezorimotor area, computing the differences between the active and the relaxation states. Phase locking value features are more discriminative in ß rhythm than in µ rhythm. The proposed method is simple, computationally efficient and proves good results on EEG Motor Movement/Imagery Dataset available from PhysioNet research resource for physiologic signals.

Keywords: brain computer interface; motor imagery task; electroencephalogram; phase locking value

Ana Loboda, Alexandra Margineanu, Gabriela Rotariu and Anca Mihaela Lazar, “Discrimination of EEG-Based Motor Imagery Tasks by Means of a Simple Phase Information Method” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 3(10), 2014. http://dx.doi.org/10.14569/IJARAI.2014.031002

@article{Loboda2014,
title = {Discrimination of EEG-Based Motor Imagery Tasks by Means of a Simple Phase Information Method},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2014.031002},
url = {http://dx.doi.org/10.14569/IJARAI.2014.031002},
year = {2014},
publisher = {The Science and Information Organization},
volume = {3},
number = {10},
author = {Ana Loboda and Alexandra Margineanu and Gabriela Rotariu and Anca Mihaela Lazar}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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