Classification of Mental Task EEG Signals Using Wavelet Packet Entropy and SVM

@article{Zhiwei2007ClassificationOM,
  title={Classification of Mental Task EEG Signals Using Wavelet Packet Entropy and SVM},
  author={Li Zhiwei and Shen Minfen},
  journal={2007 8th International Conference on Electronic Measurement and Instruments},
  year={2007},
  pages={3-906-3-909}
}
This paper address on the classification of mental task EEG signals, which is one of the key issues of Brain-Computer Interface (BCI). We proposed a method using wavelet packet entropy and Support Vector Machine (SVM). First, we apply 7 levels wavelet packet decomposition to each channel of EEG with db4. After extraction four spectrum bands (delta,thetas,alpha, beta), an entropy algorithm was performed on each bands. The resulting entropy vectors are then used as inputs to SVM to train and test… CONTINUE READING
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Wavelet Packet Entropy Used in EEG Signal Analysis

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New method on data mining: support vector machine

  • Deng Naiyang, Tian Yingjie
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2 Excerpts

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