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Analysis of Scaling Exponents of Waken and Sleeping Stage in EEG

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Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence (IWANN 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2084))

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Abstract

A classic problem in physics is the analysis of highly nonstationary time series that typically exhibit long-range correlations. Here we tested the hypothesis that the scaling exponents of the dynamics of sleeping EEG have more stable pattern than those of waken EEG by analyzing its fluctuations. We calculated the modified fluctuations of EEG stage with detrended fluctuation analysis(DFA). DFA is very useful to detect a long-range correlation in the time-series. We found a scaling exponent of sleeping stage is larger than that of waken.

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References

  1. Gandhimohan M. Viswanathan, C.-K. Peng, H. Eugene Stanley, and A. L. Goldberger: Deviations from uniform power law scaling in nonstationary time series. Phys. Rev. E 55 (1997) 845–849

    Google Scholar 

  2. Plamen Ch. Ivanov, Michael G. Rosenblum, C.-K. Peng, Joseph Mietus, Shlomo Havlin, H. Eugene Stanley, and A. L. Goldberger: Scaling behavior of heartbeat intervals obtained by wavelet-based time-series analysis. Nature 383. (1996) 323–327

    Article  Google Scholar 

  3. C.-K. Peng, Havlin S, H. E. Stanley, A. L. Goldberger: Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. Chaos. 5 (1995) 82–87

    Article  Google Scholar 

  4. Mandelbrot, B. B.: The Fractal Geometry of Nature. San Francisco, CA, Freeman. (1982)

    MATH  Google Scholar 

  5. Keshner, M. S.: 1/f Noise. Proc. IEEE, 70 (1982) 212–218

    Article  Google Scholar 

  6. Pentland, A. P.: Fractal-Based Description of Natural Scenes. IEEE Trans. Pattern Anal. Machine Intell. 6, (1984) 661–674

    Article  Google Scholar 

  7. S. V. Buldyrev, A. L. Goldberger, S. Havlin, C.-K. Peng, and H. E. Stanley: in Fractals in Science, edited by A. Bunde and S. Havlin (Springer-Verlag, Berlin, 1994) 48–87

    Google Scholar 

  8. C.-K. Peng, S. V. Buldyrev: Finite-size efforts on long-range correlations: Implications for analyzing DNA sequences. Phys. Rev. E 47 (1993) 3730-3733

    Google Scholar 

  9. E. W. Montroll, M. F. Shlesinger: in Nonequilibrium Phenomena II. From Stochastics to Hydrodynamics, edited by J. L. Lebowitz and E. W. Montroll (North-Holland, Amsterdam, 1984). 1–121.

    Google Scholar 

  10. P. Bak, C. Tang, and K. Wiesenfeld: Phys. Rev. Lett. 59 (1987) 381–384

    Article  MathSciNet  Google Scholar 

  11. J. Beran: Statistics for Long-Memory Processes. New York: Chapman & Hall. (1994)

    MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, College of Medicine, Hanyang University, Haengdang-dong, Seongdong-ku, Seoul, 133-791, Korea

    Jong-Min Lee, Dae-Jin Kim, In-Young Kim & Sun I. Kim

Authors
  1. Jong-Min Lee
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  2. Dae-Jin Kim
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  3. In-Young Kim
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  4. Sun I. Kim
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Editor information

Editors and Affiliations

  1. Departamento de Inteligencia Artificial Sanda del Rey, Universidad Nacional de Educación a Distancia, s/n., Madrid, 28040, Spain

    José Mira

  2. Departamento de Arquitectura y Tecnología de Computadores, Universidad de Granada, Campus Fuentenueva, 18071, Granada, Spain

    Alberto Prieto

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© 2001 Springer-Verlag Berlin Heidelberg

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Lee, JM., Kim, DJ., Kim, IY., Kim, S.I. (2001). Analysis of Scaling Exponents of Waken and Sleeping Stage in EEG. In: Mira, J., Prieto, A. (eds) Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence. IWANN 2001. Lecture Notes in Computer Science, vol 2084. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45720-8_53

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  • DOI: https://doi.org/10.1007/3-540-45720-8_53

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42235-8

  • Online ISBN: 978-3-540-45720-6

  • eBook Packages: Springer Book Archive

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