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Nonextensive entropy measure of EEG following brain injury from cardiac arrest

Author

Listed:
  • Tong, S.
  • Bezerianos, A.
  • Paul, J.
  • Zhu, Y.
  • Thakor, N.

Abstract

The nonextensive entropy measure is developed to study the electroencephalogram (EEG) during the recovery of the brain's electrical function from asphyxic cardiac arrest (ACA) injury. The statistical characteristics of the Tsallis-like time-dependent entropy (TDE) for different signal distributions are investigated. Both the mean and the variance of TDE show good specificity to the ACA brain injury and its recovery. ACA brain injury results in a decrease in entropy while a good electrophysiological recovery shows a rapid return to a higher entropy level. There is a reduction in the mean and increase in the variance of TDE after brain injury followed by a gradual recovery upon resuscitation. The nonextensive TDE is expected to provide a novel quantitative EEG strategy for monitoring the brain states.

Suggested Citation

  • Tong, S. & Bezerianos, A. & Paul, J. & Zhu, Y. & Thakor, N., 2002. "Nonextensive entropy measure of EEG following brain injury from cardiac arrest," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 305(3), pages 619-628.
    • Handle: RePEc:eee:phsmap:v:305:y:2002:i:3:p:619-628
    DOI: 10.1016/S0378-4371(01)00621-5
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    Cited by:

    1. Tahmasebi, S. & Longobardi, M. & Kazemi, M.R. & Alizadeh, M., 2020. "Cumulative Tsallis entropy for maximum ranked set sampling with unequal samples," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    2. Kumar, Vikas, 2016. "Some results on Tsallis entropy measure and k-record values," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 667-673.
    3. Thapliyal, Richa & Taneja, H.C. & Kumar, Vikas, 2015. "Characterization results based on non-additive entropy of order statistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 417(C), pages 297-303.
    4. Tong, Shanbao & Jiang, Dineng & Wang, Ziming & Zhu, Yisheng & Geocadin, Romeryko G. & Thakor, Nitish V., 2007. "Long range correlations in the heart rate variability following the injury of cardiac arrest," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 250-258.
    5. Nikola Gradojevic & Marko Caric, 2017. "Predicting Systemic Risk with Entropic Indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(1), pages 16-25, January.
    6. Gradojevic, Nikola & Gencay, Ramazan, 2008. "Overnight interest rates and aggregate market expectations," Economics Letters, Elsevier, vol. 100(1), pages 27-30, July.
    7. Gençay, Ramazan & Gradojevic, Nikola, 2010. "Crash of '87 -- Was it expected?: Aggregate market fears and long-range dependence," Journal of Empirical Finance, Elsevier, vol. 17(2), pages 270-282, March.
    8. Zunino, L. & Pérez, D.G. & Kowalski, A. & Martín, M.T. & Garavaglia, M. & Plastino, A. & Rosso, O.A., 2008. "Fractional Brownian motion, fractional Gaussian noise, and Tsallis permutation entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(24), pages 6057-6068.
    9. Papapetrou, M. & Kugiumtzis, D., 2020. "Tsallis conditional mutual information in investigating long range correlation in symbol sequences," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    10. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa & de Oliveira, Wilson & Stosic, Tatijana, 2016. "Foreign exchange rate entropy evolution during financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 233-239.
    11. Dagmar Markechová, 2018. "Tsallis Entropy of Fuzzy Dynamical Systems," Mathematics, MDPI, vol. 6(11), pages 1-19, November.
    12. Sunoj, S.M. & Krishnan, Aswathy S. & Sankaran, P.G., 2018. "A quantile-based study of cumulative residual Tsallis entropy measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 410-421.
    13. Kamlesh Kumar Raghuvanshi & Arun Agarwal & Amit Kumar Singh & Khushboo Jain, 2023. "Time-dependent entropic analysis of software bugs," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1718-1725, October.
    14. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa & Stosic, Tatijana, 2016. "Correlations of multiscale entropy in the FX market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 52-61.

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