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International Conference on Management Science and Engineering Management

ICMSEM 2019: Proceedings of the Thirteenth International Conference on Management Science and Engineering Management pp 295–307Cite as

Classification-Oriented Fuzzy-Rough Feature Selection for the EEG-Based Brain-Computer Interfaces

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1001))

Abstract

High-quality classification for electroencephalography (EEG) signals is a prerequisite to the use of the EEG-based brain-computer interface (BCI) technology in practical applications. Since EEG signals are non-stationary, have poor signal to noise ratio, and are contaminated with various external electromagnetic waves, it is not easy to extract the informative features of EEG signals for classification. A possible way is to integrate features from disparate channels and perspectives to capture more information. However, more features require more computational time and computer memory. In addition, some of these features do little for classification. In this paper, we adopt a fuzzy-rough selection method to select the most informative features among the candidate features. Several classifiers are used to classify the EEG signals based on the selected features. An experimental analysis illustrates the effectiveness and efficiency of the proposed approach.

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Acknowledgements

His work is supported by the Nature Science Foundation of China (No.714011 14); The Fundamental Research Funds for the Central Universities (No. skqy201524).

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Authors and Affiliations

  1. Uncertainty Decision-Making Laboratory, Sichuan University, Chengdu, 610064, People’s Republic of China

    Zhimiao Tao

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  1. Zhimiao Tao
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Correspondence to Zhimiao Tao .

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Editors and Affiliations

  1. Business School, Sichuan University, Chengdu, China

    Jiuping Xu

  2. Department of Mathematics and Statistics, Brock University on McMaster, Hamilton, ON, Canada

    Syed Ejaz Ahmed

  3. Department of Management, Monash University, Melbourne, VIC, Australia

    Fang Lee Cooke

  4. Academy of Sciences of Moldova, Chisinau, Moldova

    Gheorghe Duca

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Tao, Z. (2020). Classification-Oriented Fuzzy-Rough Feature Selection for the EEG-Based Brain-Computer Interfaces. In: Xu, J., Ahmed, S., Cooke, F., Duca, G. (eds) Proceedings of the Thirteenth International Conference on Management Science and Engineering Management. ICMSEM 2019. Advances in Intelligent Systems and Computing, vol 1001. Springer, Cham. https://doi.org/10.1007/978-3-030-21248-3_22

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