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  1. University of Yangon
  2. Department of Physics

A COMPARISON STUDY FOR AN OPTIMAL COMMON SPATIAL PATTERN ALGORITHM FOR EEG SIGNAL CLASSIFICATION APPLICABLE TO BCI SYSTEMS

http://hdl.handle.net/20.500.12678/0000002724
http://hdl.handle.net/20.500.12678/0000002724
8c5e9a11-0c7f-4808-9ad7-1f30a1dfebdf
a770762f-38b6-4af7-bef2-1b5f198c33e8
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A A Comparison study for an optimal common spatial pattern algorithm for egg signal classification applicable to BCI systems.pdf (830 Kb)
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Title
Title A COMPARISON STUDY FOR AN OPTIMAL COMMON SPATIAL PATTERN ALGORITHM FOR EEG SIGNAL CLASSIFICATION APPLICABLE TO BCI SYSTEMS
Language en
Publication date 2015
Authors
Pharino, C.
Description
Common spatial pattern (CSP), a well-known algorithm in the field of brain-computer interface (BCI), has contributed much to research in that area. Many methods have been proposed for improving classification performance using CSP. Even though there have been many CSP-based publications, there is still confusion regarding the different approaches to CSP and the important factors of each approach. This paper reviews several approaches to CSP and determines the optimal CSP parameters by analyzing electroencephalography (EEG) signals during the imagination of right-hand and foot movement tasks.
The simulation results show that a longer length of an EEG segment of 3.5-4 s is optimal for achieving the highest classification accuracy. Selecting a discriminant function for the CSP algorithm also depends on using a selection method for good optimization performance. The pair selection method can give acceptable performance with less need to care about which discriminant function is required. The maximum and minimum selection methods require
careful selection of the optimal discriminant function.
Keywords
Optimal
Identifier https://uyr.uy.edu.mm/handle/123456789/426
Journal articles
8th AUN/SEED-Net Regional Conference on Electrical and Electronics Engineering
Conference papaers
Books/reports/chapters
Thesis/dissertations
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