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Application of Empirical Mode Decomposition to Cardiorespiratory Synchronization

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Complex Dynamics in Physiological Systems: From Heart to Brain

Part of the book series: Understanding Complex Systems ((UCS))

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Abstract

A scheme based on the empirical mode decomposition (EMD) and synchrogram introduced by Wu and Hu [Phys. Rev. E 74, 051917 (2006)] to study cardiorespiratory synchronization is reviewed. In the scheme, an experimental respiratory signal is decomposed into a set of intrinsic mode functions (IMFs), and one of these IMFs is selected as a respiratory rhythm to construct the cardiorespiratory synchrogram incorporating with heartbeat data. The analysis of 20 data sets from ten young (21–34 years old) and ten elderly (68–81 years old) rigorously screened healthy subjects shows that regularity of respiratory signals plays a dominant role in cardiorespiratory synchronization.

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References

  1. A.C. Guyton, Textbook of medical physiology, 8th ed. (Saunders, Philadelphia 1991).

    Google Scholar 

  2. L. Bernardi, F. Salvucci, R. Suardi, P.L. Solda, A. Calciati, S. Perlini, C. Falcone, and L. Ricciardi, Evidence for an intrinsic mechanism regulating heart-rate-variability in the transplanted and the intact heart during submaximal dynamic exercise, Cardiovasc. Res. 24,969–981 (1990).

    Article  PubMed  CAS  Google Scholar 

  3. J. Almasi and O.H. Schmitt, Basic technology of voluntary cardiorespiratory synchronization in electrocardiology, IEEE Trans. Biomed. Eng. 21, 264–273 (1974).

    CAS  Google Scholar 

  4. P. Tass, M.G. Rosenblum, J. Weule, J. Kurths, A. Pikovsky, J. Volkmann, A. Schnitzler, and H.-J. Freund, Detection of n:m Phase Locking from Noisy Data: Application to Magnetoencephalography, Phys. Rev. Lett. 31, 3291 (1998).

    Article  Google Scholar 

  5. C. Schäfer, M.G. Rosenblum, J. Kurths, and H.-H. Abel, Heartbeat synchronized with ventilation, Nature (London) 392, 239–240 (1998).

    Article  Google Scholar 

  6. C. Schäfer, M.G. Rosenblum, H.-H. Abel, and J. Kurths, Synchronization in the human cardiorespiratory system, Phys. Rev. E 60, 857 (1999).

    Article  Google Scholar 

  7. M.G. Rosenblum, J. Kurths, A. Pikovsky, C. Schäfer, P. Tass, H.-H. Abel, Synchronization in noisy systems and cardiorespiratory interaction, IEEE Eng. Med. Biol. Mag. 17,46–53 (1998).

    Article  PubMed  CAS  Google Scholar 

  8. E. Toledo, S. Akselrod, I. Pinhas, and D. Aravot, Does synchronization reflect a true interaction in the cardiorespiratory system? Med. Eng. Phys. 24, 45–52 (2002).

    Article  PubMed  CAS  Google Scholar 

  9. E. Toledo, M.G. Roseblum, C. Schäfer, J. Kurhts, and S. Akselrod, Quantification of cardiorespiratory synchronization in normal and heart transplant subjects. In: Proc. of Int. Symposium on Nonlinear Theory and its Applications, vol. 1, Lausanne, Presses polytechniques et universitaries romandes, pp. 171–174 (1998).

    Google Scholar 

  10. E. Toledo, M.G. Rosenblum, J. Kurths, and S. Akselrod, Cardiorespiratory synchronization: is it a real phenomenon ? In: Computers in Cardiology, vol. 26, Los Alamitos (CA), IEEE Computer Society, pp. 237–240 (1999).

    Google Scholar 

  11. M.B. Lotric and A. Stefanovska, Synchronization and modulation in the human cardiorespiratory system, Physica A 283, 451–461 (2000).

    Article  Google Scholar 

  12. R. Mrowka and A. Patzak, Quantitative analysis of cardiorespiratory synchronization in infants, Int. J. Bifurcation and Chaos 10, 2479–2488 (2000).

    Google Scholar 

  13. A. Stefanovska, H. Haken, P.V.E. McClintock, M. Hozic, F. Bajrovic, and S. Ribaric, Reversible transitions between synchronization states of the cardiorespiratory system, Phys. Rev. Lett. 85, 4831 (2000).

    Article  PubMed  CAS  Google Scholar 

  14. K. Kotani, K. Takamasu, Y. Ashkenazy, H.E. Stanley, and Y. Yamamoto, Model for cardiorespiratory synchronization in humans, Phys. Rev. E 65, 051923 (2002).

    Article  CAS  Google Scholar 

  15. M.G. Rosenblum, A.S. Pikovsky, and J. Kurths, Phase synchronization of chaotic oscillators, Phys. Rev. Lett. 76, 1804 (1996).

    Article  PubMed  CAS  Google Scholar 

  16. R. Q. Quiroga, J. Arnhold, and P. Grassberger, Learning driver-response relationships from synchronization patterns, Phys. Rev. E 61, 5142 (2000).

    Article  CAS  Google Scholar 

  17. R.Q. Quiroga, A. Kraskov, T. Kreuz, and P.P. Grassberger, Performance of different synchronization measures in real data: A case study on electroencephalographic signals, Phys. Rev. E 65, 041903 (2002).

    Article  CAS  Google Scholar 

  18. M.G. Rosenblum, A.S. Pikovsky, and J. Kurths, Synchronization approach to analysis of biological systems, Fluctuation and Noise Lett. 4, L53–L62 (2004).

    Article  Google Scholar 

  19. M.G. Rosenblum and A.S. Pikovsky, Controlling synchronization in an ensemble of globally coupled oscillators, Phys. Rev. Lett. 92, 114102 (2004).

    Article  PubMed  CAS  Google Scholar 

  20. T. Schreiber, Measuring information transfer, Phys. Rev. Lett. 85, 461 (2000).

    Article  PubMed  CAS  Google Scholar 

  21. M. Paluš and A. Stefanovska, Direction of coupling from phases of interacting oscillators: An information-theoretic approach, Phys. Rev. E 67, 055201(R) (2003).

    Article  CAS  Google Scholar 

  22. J. Jamsek and A. Stefanovska, P.V.E. McClintock, Nonlinear cardio-respiratory interactions revealed by time-phase bispectral analysis, Phys. Med. Bio. 49, 4407–4425 (2004).

    Article  Google Scholar 

  23. M. Richter, T. Schreiber, and D.T. Kaplan, Fetal ECG extraction with nonlinear state-space projections, IEEE Eng. Med. Biol. Mag. 45, 133–137 (1998).

    CAS  Google Scholar 

  24. R. Hegger, H. Kantz, and T. Schreiber, Practical implementation of nonlinear time series methods: The TISEAN package, Chaos 9, 413–435 (1999).

    Article  Google Scholar 

  25. H. Kantz and T. Schreiber, Human EGG: Nonlinear deterministic versus stochastic aspects, IEE Proceedings – Science Measurement and Technology 145, 279–284 (1998).

    Article  Google Scholar 

  26. M.-C. Wu and C.-K. Hu, Empirical mode decomposition and synchrogram approach to cardiorespiratory synchronization, Phys. Rev. E 73, 051917 (2006).

    Article  CAS  Google Scholar 

  27. D. Gabor, Theory of communication, J. Inst. Electron Eng. 93, 429–457 (1946).

    Google Scholar 

  28. S. Blanco, R. Q. Quiroga, O.A. Rosso, and S.Kochen, Time-frequency analysis of electroencephalogram series, Phys. Rev. E 51, 2624 (1995).

    Article  CAS  Google Scholar 

  29. S. Blanco, C.E. D’Attellis, S.I. Isaacson, O.A.Rosso, and R.O. Sirne, Time-frequency analysis of electroencephalogram series. II. Gabor and wavelet transforms, Phys. Rev. E 54, 6661 (1996).

    Article  CAS  Google Scholar 

  30. S. Blanco, A. Figliola, R.Q. Quiroga, O.A. Rosso, and E. Serrano, Time-frequency analysis of electroencephalogram series. III. Wavelet packets, Phys. Rev. E 57, 932 (1998).

    Article  CAS  Google Scholar 

  31. K. Ohashi, L.A.H. Amaral, B.H. Natelson, and Y. Yamamoto, Asymmetrical singularities in real-world signals, Phys. Rev. E 68, 065204(R) (2003).

    Article  CAS  Google Scholar 

  32. K. Karhunen, Uber lineare methoden in der wahrscheinlichkeits-rechnung, Ann. Acad. Sci. Fennicae, ser. A1, Math. Phys. 37 (1946).

    Google Scholar 

  33. M.M. Loéve, Probability theory, Princeton, NJ, Van Nostrand (1955).

    Google Scholar 

  34. N.E. Huang, Z. Shen, S.R. Long, M.C. Wu, H.H. Shih, Q. Zheng, N.-C. Yen, C.-C. Tung, and H.H. Liu, The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proc. R. Soc. Lond. A 454, 903–995 (1998).

    Google Scholar 

  35. N. Iyengar, C.-K. Peng, R. Morin, A. L. Goldberger, and L. A. Lipsitz, Age-related alterations in the fractal scaling of cardiac interbeat interval dynamics, Am. J. Physiol. 271, 1078–1084 (1996). Data sets are available from http://physionet.org/physiobank/database/fantasia/

    Google Scholar 

  36. N.E. Huang, M.C. Wu, S.R. Long, S.S. P. Shen, W. Qu, P. Gloersen, and K.L. Fan, A confidence limit for the empirical mode decomposition and Hilbert spectral analysis, Proc. R. Soc. Lond. A 459, 2317–2345 (2003).

    Google Scholar 

  37. M. G. Roseblum and A. S. Pikovsky, Detecting direction of coupling in interacting oscillators, Phys. Rev. E 64, 045202(R) (2001).

    Article  CAS  Google Scholar 

  38. M.-C. Wu, M.-C. Huang, Y.-C. Yu, and T. C. Chiang, Phase distribution and phase correlation of financial time series, Phys. Rev. E 73, 016118 (2006).

    Article  CAS  Google Scholar 

  39. M.-C. Wu, Phase correlation of foreign exchange time series, Physica A 375, 633–642 (2007).

    Article  Google Scholar 

  40. M.-C. Wu, Phase statistics approach to time series analysis, J. Korean Phys. Soc. 50,304–312 (2007).

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Research Center for Adaptive Data Analysis, National Central University, Chungli 32001, Taiwan

    Ming-Chya Wu

Authors
  1. Ming-Chya Wu
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  2. Chin-Kun Hu
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Editor information

Editors and Affiliations

  1. Central Instrumentation, Indian Institute of Chemical Biology, Kolkata-700032, India

    Syamal K. Dana (Dr.) (Dr.)

  2. Department of Physics, Presidency College, Kolkata-700073, India

    Prodyot K. Roy (Dr.) (Dr.)

  3. Institut für Physik, Universität Potsdam, Am Neuen Palais 10, 14415, Potsdam, Germany

    Jürgen Kurths (Dr.) (Dr.)

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Wu, MC., Hu, CK. (2009). Application of Empirical Mode Decomposition to Cardiorespiratory Synchronization. In: Dana, S.K., Roy, P.K., Kurths, J. (eds) Complex Dynamics in Physiological Systems: From Heart to Brain. Understanding Complex Systems. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9143-8_11

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