EEG Feature Extraction and Pattern Classification Based on Motor Imagery in Brain-Computer Interface
2011 ◽
Vol 3
(3)
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pp. 43-56
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Keyword(s):
Accurate classification of EEG left and right hand motor imagery is an important issue in brain-computer interface. Firstly, discrete wavelet transform method was used to decompose the average power of C3 electrode and C4 electrode in left-right hands imagery movement during some periods of time. The reconstructed signal of approximation coefficient A6 on the sixth level was selected to build up a feature signal. Secondly, the performances by Fisher Linear Discriminant Analysis with two different threshold calculation ways and Support Vector Machine methods were compared. The final classification results showed that false classification rate by Support Vector Machine was lower and gained an ideal classification results.
2011 ◽
Vol 2011
◽
pp. 1-8
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2012 ◽
Vol 20
(4)
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pp. 526-538
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Keyword(s):
2019 ◽
Vol 2019
◽
pp. 1-16
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Keyword(s):
2016 ◽
Vol 2016
◽
pp. 1-15
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2021 ◽
Vol 11
(12)
◽
pp. 2918-2927
2006 ◽
pp. 701-706
Keyword(s):