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

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.

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Cite this paper

@article{Li2010TheFE, title={The Feature Extraction and Recognition of Transient Visual Evoked Potential Based on Wavelet Transform}, author={Ming-Ai Li and Fang-kun Zhang and Jin-Fu Yang}, journal={2010 International Conference on Biomedical Engineering and Computer Science}, year={2010}, pages={1-4} }