The Feature Extraction and Recognition of Transient Visual Evoked Potential Based on Wavelet Transform

Author

Li Ming-Ai ; Zhang Fang-kun ; Yang Jin-Fu

Author_Institution

Instn. of Artificial Intell. & Robot, Beijing Univ. of Technol., Beijing, China

fYear

2010

fDate

23-25 April 2010

Firstpage

1

Lastpage

4

Abstract

Based on the B-spline wavelet transform and BP neural network, a method was proposed to extract and recognize the features of transient visual evoked potential in the brain-computer interface system. Based on the analysis of brain frequency domain mapping, this paper carried out a new averaging pre-treatment method to Transient visual evoked potential (TVEP) in order to enhance the signal-noise ratio; Then, based on the B-spline wavelet transform to extract the features and design a BP Neural Network Classifier; At last, study on the TVEP data collect by experiment, obtain a higher recognition rate and verify the correctness and effectiveness of this method.

Keywords

backpropagation; brain-computer interfaces; feature extraction; neural nets; splines (mathematics); visual evoked potentials; wavelet transforms; B-spline wavelet transform; BP neural network classifier; brain frequency domain mapping; brain-computer interface system; feature extraction; signal-noise ratio; transient visual evoked potential recognition; Biological neural networks; Brain computer interfaces; Feature extraction; Frequency domain analysis; Signal analysis; Signal mapping; Spline; Transient analysis; Wavelet analysis; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Computer Science (ICBECS), 2010 International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-5315-3

Type

conf

DOI

10.1109/ICBECS.2010.5462347

Filename

5462347