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A Study of Sleep Stages Threshold Based on Multiscale Fuzzy Entropy

  • Xuexiao Shao
  • Bin Hu
  • Yalin Li
  • Xiangwei Zheng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11336)

Abstract

The classification of sleep stages based on EEG signals has become a prerequisite for monitoring sleep quality and diagnosing sleep-related diseases. Many researchers have conducted related research work. But, they often overlook the effect of the extracted characteristics on actual sleep staging results and the interpretation in psychology and clinical medicine. Therefore, this study calculates the value of multiscale fuzzy entropy as evaluation criteria and measures the threshold range of sleep stage based on CEEMDAN algorithm and psychophysics method. The experimental results show that the proposed method can effectively distinguish between different sleep stages by using fuzzy entropy as a measure of sleep staging thresholds. In addition, we designed a set of comparative experiments based on the single-channel EEG sample data and studied the gender factor on sleep stages by comparing sleep entropy thresholds of different genders. It was found that the sleep threshold of female was significantly greater than male.

Keywords

CEEMDAN Sleep stages Multiscale fuzzy entropy Threshold 

Notes

Acknowledgments

National Natural Science Foundation of China (61373149) and the Taishan Scholars Program of Shandong Province, China.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Xuexiao Shao
    • 1
    • 2
  • Bin Hu
    • 1
    • 2
  • Yalin Li
    • 1
    • 3
  • Xiangwei Zheng
    • 1
    • 2
  1. 1.School of Information Science and EngineeringShandong Normal UniversityJinanChina
  2. 2.Shandong Provincial Key Laboratory for Distributed Computer Software Novel TechnologyJinanChina
  3. 3.School of Information EngineeringShandong Management UniversityJinanChina

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