INFORMATION CHANGE THE WORLD

International Journal of Education and Management Engineering(IJEME)

ISSN: 2305-3623 (Print), ISSN: 2305-8463 (Online)

Published By: MECS Press

IJEME Vol.1, No.6, Dec. 2011

Research of P300 Feature Extraction Algorithm Based on Wavelet Transform and Fisher Distance

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Author(s)

WANG Pan, SHEN Ji-Zhong, SHEN Jin-He

Index Terms

BCI; Wavelet Transform; P300; Fisher Distance; Feature Extraction

Abstract

With the aim to improve the divisibility of the features extracted by wavelet transform in P300 detection, we research the P300 frequency domain of event related potentials and the influence of mother wavelet selection towards the divisibility of extracted features, and then a new P300 feature extraction method based on wavelet transform and Fisher distance is proposed, which overcomes the drawbacks of no systematic feature selection method during traditional P300 feature extraction based on wavelet transform. In this paper, both the BCI Competition 2003 and the BCI Competition 2005 data sets of P300 were used for validation, the results showed that the proposed method can increase the divisibility by 121.8% of the features extracted by wavelet transform, and contribute to the followed classification.

Cite This Paper

WANG Pan, SHEN Ji-Zhong, SHEN Jin-He,"Research of P300 Feature Extraction Algorithm Based on Wavelet Transform and Fisher Distance", IJEME, vol.1, no.6, pp.36-43, 2011.

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