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On multiscale entropy analysis for physiological data

Author

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  • Thuraisingham, Ranjit A.
  • Gottwald, Georg A.

Abstract

We perform an analysis of cardiac data using multiscale entropy as proposed in Costa et al. [Multiscale entropy analysis of complex physiological time series, Phys. Rev. Lett. 89 (2002) 068102]. We reproduce the signatures of the multiscale entropy for the three cases of young healthy hearts, atrial fibrillation and congestive heart failure. We show that one has to be cautious how to interpret these signatures in terms of the underlying dynamics. In particular, we show that different dynamical systems can exhibit the same signatures depending on the sampling time, and that similar systems may have different signatures depending on the time scales involved. Besides the total amount of data we identify the sampling time, the correlation time and the period of possible nonlinear oscillations as important time scales which have to be involved in a detailed analysis of the signatures of multiscale entropies. We illustrate our ideas with the Lorenz equation as a simple deterministic chaotic system.

Suggested Citation

  • Thuraisingham, Ranjit A. & Gottwald, Georg A., 2006. "On multiscale entropy analysis for physiological data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 323-332.
  • Handle: RePEc:eee:phsmap:v:366:y:2006:i:c:p:323-332
    DOI: 10.1016/j.physa.2005.10.008
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    References listed on IDEAS

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    1. Säkki, M & Kalda, J & Vainu, M & Laan, M, 2004. "The distribution of low-variability periods in human heartbeat dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 255-260.
    2. Chi-Sang Poon & Christopher K. Merrill, 1997. "Decrease of cardiac chaos in congestive heart failure," Nature, Nature, vol. 389(6650), pages 492-495, October.
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    Cited by:

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    3. Yin, Yi & Shang, Pengjian & Ahn, Andrew C. & Peng, Chung-Kang, 2019. "Multiscale joint permutation entropy for complex time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 388-402.
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    7. Litak, Grzegorz & Abadal, Gabriel & Rysak, Andrzej & Przywara, Hubert, 2017. "Complex dynamics of a bistable electrically charged microcantilever: Transition from single well to cross well oscillations," Chaos, Solitons & Fractals, Elsevier, vol. 99(C), pages 85-90.
    8. Zhang, Bo & Wang, Jun & Fang, Wen, 2015. "Volatility behavior of visibility graph EMD financial time series from Ising interacting system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 301-314.
    9. Chen, Shijian & Shang, Pengjian & Wu, Yue, 2018. "Weighted multiscale Rényi permutation entropy of nonlinear time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 548-570.
    10. Tian, Qiang & Shang, Pengjian & Feng, Guochen, 2014. "Financial time series analysis based on information categorization method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 183-191.
    11. Yin, Yi & Wang, Xi & Li, Qiang & Shang, Pengjian, 2020. "Generalized multivariate multiscale sample entropy for detecting the complexity in complex systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    12. Zhang, Yali & Shang, Pengjian & He, Jiayi & Xiong, Hui, 2020. "Cumulative Tsallis entropy based on multi-scale permuted distribution of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).

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    Keywords

    Multiscale entropy; Cardiac arrhythmias;

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