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Multiscale Entropy Analysis of EEG Based on Non-uniform Time

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Pattern Recognition and Computer Vision (PRCV 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11858))

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Abstract

To address the problem of loss of time series information when taking the mean value of the average signal from EEG data, a variance index is used to reconstruct the time series, and a multi-scale entropy method based on a non-uniform time window is proposed. The effectiveness of the method is verified in two data sets. The results show that the use of the variance of multi-scale time series can extract more effective features compared with average indicators. Compared with coarse-grained methods, the fine-grained method has better accuracy, but its time complexity is also higher. The uniform time window method has not only better accuracy, but also reduced time complexity.

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Acknowledgments

This study was supported by research grants from the National Natural Science Foundation of China (61472270, 61672374, 61741212), Natural Science Foundation of Shanxi Province (201601D021073, 201801D121135), and Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi (2016139).

Author information

Authors and Affiliations

  1. Taiyuan University of Technology, Taiyuan, 030024, China

    Hongxia Deng, Jinxiu Guo, Xiaofeng Yang, Jinxiu Hou & Haifang Li

  2. North China Electric Power University, Beijing, 102206, China

    Haoqi Liu

Authors
  1. Hongxia Deng
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  2. Jinxiu Guo
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  3. Xiaofeng Yang
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  4. Jinxiu Hou
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  5. Haoqi Liu
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  6. Haifang Li
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Corresponding author

Correspondence to Haifang Li .

Editor information

Editors and Affiliations

  1. School of EECS, Peking University, Beijing, China

    Zhouchen Lin

  2. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Liang Wang

  3. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

  4. Xidian University, Xi'an, China

    Guangming Shi

  5. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Tieniu Tan

  6. Institute of Artificial Intelligence, Xi'an Jiaotong University, Xi'an, China

    Nanning Zheng

  7. Chinese Academy of Sciences, Beijing, China

    Xilin Chen

  8. Northwestern Polytechnical University, Xi'an, China

    Yanning Zhang

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Deng, H., Guo, J., Yang, X., Hou, J., Liu, H., Li, H. (2019). Multiscale Entropy Analysis of EEG Based on Non-uniform Time. In: Lin, Z., et al. Pattern Recognition and Computer Vision. PRCV 2019. Lecture Notes in Computer Science(), vol 11858. Springer, Cham. https://doi.org/10.1007/978-3-030-31723-2_1

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  • DOI: https://doi.org/10.1007/978-3-030-31723-2_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-31722-5

  • Online ISBN: 978-3-030-31723-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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