Relative wavelet bispectrum feature for alcoholic EEG signal classification using artificial neural network

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper proposes a novel relative wavelet bispectrum (RWB) approach for EEG signal feature extraction method to differentiate the signal between the alcoholic over the non-alcoholic subjects. Firstly, the EEG signal is calculated for its autocorrelation frequencies as the basic step in the bispectrum calculation. Then, the discrete wavelet transform (DWT) is applied substituting the FFT which usually is used in the bispectrum calculation. Lastly, the relative value of each frequency band is calculated for both the approximation and the details parts, producing the RWB. The proposed methodology is implemented in an alcoholic automated detection system using 1200 data samples from UCI EEG Database for alcoholism. Based on the experiments, the setting value of lag in the autocorrelation calculation was evidently very influential on the recognition rate obtained, i.e. the maximum value for the lag was the best. Using cross validation, the highest results from RWB feature extraction method with ANN classifier achieved about 90% recognition rate.

Original languageEnglish
Title of host publicationQiR 2017 - 2017 15th International Conference on Quality in Research (QiR)
Subtitle of host publicationInternational Symposium on Electrical and Computer Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages154-158
Number of pages5
ISBN (Electronic)9781509063970
DOIs
Publication statusPublished - 5 Dec 2017
Event15th International Conference on Quality in Research: International Symposium on Electrical and Computer Engineering, QiR 2017 - Nusa Dua, Bali, Indonesia
Duration: 24 Jul 201727 Jul 2017

Publication series

NameQiR 2017 - 2017 15th International Conference on Quality in Research (QiR): International Symposium on Electrical and Computer Engineering
Volume2017-December

Conference

Conference15th International Conference on Quality in Research: International Symposium on Electrical and Computer Engineering, QiR 2017
CountryIndonesia
CityNusa Dua, Bali
Period24/07/1727/07/17

Keywords

  • alcohol
  • artificial neural networks
  • automatic recognition
  • bispectrum
  • Electroencephalogram
  • wavelet

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