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Motor Imagery EEG Feature Extraction Based on Fuzzy Entropy with Wavelet Transform

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The 10th International Conference on Computer Engineering and Networks (CENet 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1274))

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Abstract

Due to the nonlinear characteristics of EEG signals and the rhythm characteristics of motor imagery, the low recognition rate of using single feature extraction algorithm, a feature extraction method based on wavelet transform and fuzzy entropy is presented in this paper. The EEG signals are decomposed to three levels by the wavelet transform, according to the ERS/ERD phenomena during motor imagery, the alpha rhythm and beta rhythm signal can be extracted by the algorithm of fuzzy entropy. Finally, the motor imagery EEG signals are classified by a support vector machine classifier. BCI Competition IV Datasets1 has been used to conduct the experiment, the experimental results show that the feature extraction method combining wavelet transform and fuzzy entropy is much better than the ways of using single fuzzy entropy, sample entropy, or others, and its highest recognition rate is 90.25%.

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Acknowledgement

This research was funded by the National Natural Science Foundation of China (Nos. 61871427 and 61372023).

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Authors and Affiliations

  1. Institute of Intelligent Control and Robotics, Hangzhou Dianzi University, Hangzhou, 310018, China

    Tao Yang, Yuliang Ma, Ming Meng & Qingshan She

Authors
  1. Tao Yang
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  2. Yuliang Ma
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  3. Ming Meng
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  4. Qingshan She
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Corresponding author

Correspondence to Yuliang Ma .

Editor information

Editors and Affiliations

  1. Science and Technology, Nanjing University of Information, Nanjing, Jiangsu, China

    Qi Liu

  2. School of Computing, Edinburgh Napier University, Edinburgh, UK

    Xiaodong Liu

  3. School of Electrical Engineering, University of Jinan, Jinan, Shandong, China

    Tao Shen

  4. Institute of Network Technology, Beijing University of Posts and Telecommunications, Beijing, Beijing, China

    Xuesong Qiu

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Yang, T., Ma, Y., Meng, M., She, Q. (2021). Motor Imagery EEG Feature Extraction Based on Fuzzy Entropy with Wavelet Transform. In: Liu, Q., Liu, X., Shen, T., Qiu, X. (eds) The 10th International Conference on Computer Engineering and Networks. CENet 2020. Advances in Intelligent Systems and Computing, vol 1274. Springer, Singapore. https://doi.org/10.1007/978-981-15-8462-6_190

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  • DOI: https://doi.org/10.1007/978-981-15-8462-6_190

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-8461-9

  • Online ISBN: 978-981-15-8462-6

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