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Combination of Frequency Bands in EEG for Feature Reduction in Mental Task Classification

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2 Author(s)
Farnaz Abdollahi ; Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran, Iran. E-mail: ; Ali Motie-Nasrabadi

Brain-computer interfaces require online processing of electroencephalogram (EEG) measurements. Therefore, speed of signal processing is of great importance in BCI systems. We present a method of feature reduction by combining frequency band powers of EEG, in order to speed up processing and meanwhile avoid classifier overfitting. As a result a linear combination of power spectrum of EEG frequency bands (alpha, beta, gamma, delta & theta) was found that reduces the dimension of feature vector by a factor of 5. This method gives a total correct classification rate of 91.71% comparing to 87.96% achieved from direct use of frequency band powers and 85.54% achieved from PCA feature reduction method applied to the same feature vector with 14 components

Published in:

Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE

Date of Conference:

Aug. 30 2006-Sept. 3 2006