Feature Extraction by Combining Wavelet Packet Transform and Common Spatial Pattern in Brain-Computer Interfaces

Ren Xiang Han; Qing Guo Wei

doi:10.4028/www.scientific.net/AMM.239-240.974

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 239-240Feature Extraction by Combining Wavelet Packet...

Feature Extraction by Combining Wavelet Packet Transform and Common Spatial Pattern in Brain-Computer Interfaces

Abstract:

Wavelet packet transform (WPT) and common spatial pattern (CSP) are two commonly used methods for feature extraction in brain-computer interfaces. In this paper, a new feature extraction method was proposed that was based on the combination of WPT and CSP. The raw EEG signals were band pass filtered between 8 and 30Hz, then the filtered signals were subject to WPT and reconstruction, and finally the reconstructed signals were spatially filtered by CSP algorithm. The proposed algorithm was applied to six data sets recorded during BCI experiments based on motor imagery. The results showed superior classification performance, thus verifying the feasibility and validity of the algorithm.

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Periodical:

Applied Mechanics and Materials (Volumes 239-240)

Pages:

974-979

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.239-240.974

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Online since:

December 2012

Authors:

Ren Xiang Han, Qing Guo Wei

Keywords:

Brain Computer Interface (BCI), Common Spatial Pattern, Feature Extraction, Wavelet Packet Transform

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