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Brain-Computer Interface Using Wavelet Transformation and Naïve Bayes Classifier

Part of the Advances in Experimental Medicine and Biology book series (AEMB,volume 657)

Abstract

The main purpose of this work is to establish an exploratory approach using electroencephalographic (EEG) signal, analyzing the patterns in the time-frequency plane. This work also aims to optimize the EEG signal analysis through the improvement of classifiers and, eventually, of the BCI performance. In this paper a novel exploratory approach for data mining of EEG signal based on continuous wavelet transformation (CWT) and wavelet coherence (WC) statistical analysis is introduced and applied. The CWT allows the representation of time-frequency patterns of the signal’s information content by WC qualiatative analysis. Results suggest that the proposed methodology is capable of identifying regions in time-frequency spectrum during the specified task of BCI. Furthermore, an example of a region is identified, and the patterns are classified using a Naïve Bayes Classifier (NBC). This innovative characteristic of the process justifies the feasibility of the proposed approach to other data mining applications. It can open new physiologic researches in this field and on non stationary time series analysis.

Keywords

  • Pattern analysis
  • Classification
  • Signal processing
  • Brain computer interface

This work was supported in part by CAPES (Coordenadoria de Aperfeiçoamento de pessoal de Nível Superior) and PUCPR (Pontifícia Universidade Católica do Paraná).

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Acknowledgements

The authors acknowledge Ph.D. Elisangela F. Manffra, Ph.D. Luiz R. Aguiar, and M.Sc. Guilherme Nogueira for the fruitful discussions. Also a special thanks for the Laboratory of Rehabilitation Engineering (LER) Research Group at PUCPR.

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Correspondence to Julio Cesar Nievola .

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Bassani, T., Nievola, J.C. (2010). Brain-Computer Interface Using Wavelet Transformation and Naïve Bayes Classifier. In: Hussain, A., Aleksander, I., Smith, L., Barros, A., Chrisley, R., Cutsuridis, V. (eds) Brain Inspired Cognitive Systems 2008. Advances in Experimental Medicine and Biology, vol 657. Springer, New York, NY. https://doi.org/10.1007/978-0-387-79100-5_8

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