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2020 | OriginalPaper | Chapter

Cardiorespiratory Coupling: A Review of the Analysis Methods

Authors : V. Tonu, V. Vovc, N. Enache

Published in: 4th International Conference on Nanotechnologies and Biomedical Engineering

Publisher: Springer International Publishing

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Abstract

Interaction between cardiovascular and respiratory systems were studied intensively over the last few decades, in order to understand the principles of cardiorespiratory interactions in healthy and non-healthy subjects. Different physiological conditions such as REM sleep, anesthesia, stress, post-stress were used in order to determine and analyze the hidden parameters, that regulate the synchronization between these two integrated physiological systems and their behavior. This paper aims to review the most common methods of analysis of the cardiorespiratory coupling and their capacity to provide additional information for diagnosis and prognosis in medicine.

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Mensah, G.A., et al.: Decline in cardiovascular mortality: possible causes and implications. Circ. Res. 120(2), 366–380 (2017)MathSciNetCrossRef

Seidel, H., Herzel, H.: Modelling heart rate variability due to respiration and baroreflex BT–modelling the dynamics of biological systems: nonlinear phenomena and pattern formation. In: Mosekilde, E., Mouritsen, O.G. (eds.) pp. 205–229. Springer, Berlin, Heidelberg (1995)

Amaral, L.A.N., et al.: Behavioral-independent features of complex heartbeat dynamics. Phys. Rev. Lett. 86(26), 6026 (2001)CrossRef

Choi J., Gutierrez-Osuna, R.: Estimating mental stress using a wearable cardio-respiratory sensor, In: Sensors, 2010 IEEE, pp. 150–154 (2010)

Tan, C.O., Cohen, M.A., Eckberg, D.L., Taylor, J.A.: Fractal properties of human heart period variability: physiological and methodological implications. J. Physiol. 587(Pt 15), 3929–3941 (2009)CrossRef

Huikuri, H.V., Perkiömäki, J.S., Maestri, R., Pinna, G.D.: Clinical impact of evaluation of cardiovascular control by novel methods of heart rate dynamics. Philos. Trans. R. Soc. Math. Phys. Eng. Sci. 367(1892), 1223–1238 (2009)CrossRef

Stefanovska, A.: Coupled oscillators: complex but not complicated cardiovascular and brain interactions. In: 2006 International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 437–440 (2006)

Milhorn Jr., H.T., Benton, R., Ross, R., Guyton, A.C.: A mathematical model of the human respiratory control system. Biophys. J. 5(1), 27 (1965)CrossRef

Chang, H.K.: Respiratory physiology: an analytical approach, vol. 40. Marcel Dekker (1989)

10.

Ursino, M., Magosso, E.: Short-term autonomic control of cardiovascular function: a mini-review with the help of mathematical models. J. Integr. Neurosci. 2(02), 219–247 (2003)CrossRef

11.

Dickinson, C.J.: A computer model of human respiration: ventilation, blood gas transport and exchange, hydrogen ion regulation: for teaching, research and clinical use, “MacPuf”. University park press (1977)

12.

Duffin, J., Mohan, R.M., Vasiliou, P., Stephenson, R., Mahamed, S.: A model of the chemoreflex control of breathing in humans: model parameters measurement. Respir. Physiol. 120(1), 13–26 (2000)CrossRef

13.

Schäfer, C., Rosenblum, M.G., Abel, H.-H., Kurths, J.: Synchronization in the human cardiorespiratory system. Phys. Rev. E 60(1), 857 (1999)CrossRef

14.

Jensen-Urstad, K., Storck, N., Bouvier, F., Ericson, M., Lindblad, L.E., Jensen-Urstad, M.: Heart rate variability in healthy subjects is related to age and gender, 60 (1997)

15.

Michael Crump, outcomes in refractory aggressive diffuse large b-cell lymphoma (DLBCL): results from the international SCHOLAR-1 study. ASCO 2016, abstract 7516CrossRef

16.

Schulz, S., et al.: Cardiovascular and cardiorespiratory coupling analyses: a review. 371 (2013)

17.

Faes, L., Nollo, G.: Extended causal modeling to assess partial directed coherence in multiple time series with significant instantaneous interactions. Biol. Cybern. 103(5), 387–400 (2010)MathSciNetCrossRef

18.

Ancona, N., Marinazzo, D., Stramaglia, S.: Radial basis function approach to nonlinear Granger causality of time series. Phys. Rev. E 70(5), 56221 (2004)CrossRef

19.

Porta, A., et al.: Model-based assessment of baroreflex and cardiopulmonary couplings during graded head-up tilt. Comput. Biol. Med. 42(3), 298–305 (2012)MathSciNetCrossRef

20.

Shannon, C.E.: A mathematical theory of communication. Bell Syst. Tech. J. 27(3), 379–423 (1948)MathSciNetCrossRef

21.

Borowska, M.: Entropy-based algorithms in the analysis of biomedical signals. Stud. Log., Gramm. Rhetor. 43(1), 21–32 (2015)CrossRef

22.

Pincus, S.M.: Approximate entropy as a measure of system complexity. Proc. Natl. Acad. Sci. 88(6), 2297–2301 (1991)MathSciNetCrossRef

23.

Cohen, A., Procaccia, I.: Computing the Kolmogorov entropy from time signals of dissipative and conservative dynamical systems. Phys. Rev. A 31(3), 1872 (1985)CrossRef

24.

Porta, A., et al.: Measuring regularity by means of a corrected conditional entropy in sympathetic outflow. Biol. Cybern. 78(1), 71–78 (1998)CrossRef

25.

Porta, A., Baselli, G., Lombardi, F., Montano, N., Malliani, A., Cerutti, S.: Conditional entropy approach for the evaluation of the coupling strength. Biol. Cybern. 81(2), 119–129 (1999)CrossRef

26.

Fan, J., Yao, Q.: Nonlinear time series: nonparametric and parametric methods. Springer Science & Business Media (2008)

27.

Faes, L., Nollo, G.: Bivariate nonlinear prediction to quantify the strength of complex dynamical interactions in short-term cardiovascular variability. Med. Biol. Eng. Comput. 44(5), 383–392 (2006)CrossRef

28.

Farmer, J.D., Sidorowich, J.J.: Predicting chaotic time series. Phys. Rev. Lett. 59(8), 845 (1987)MathSciNetCrossRef

29.

Faes, L., Porta, A., Nollo, G.: Mutual nonlinear prediction as a tool to evaluate coupling strength and directionality in bivariate time series: comparison among different strategies based on $k$ nearest neighbors. Phys. Rev. E 78(2), 26201 (2008)CrossRef

30.

Baumert, M., Walther, T., Hopfe, J., Stepan, H., Faber, R., Voss, A.: Joint symbolic dynamic analysis of beat-to-beat interactions of heart rate and systolic blood pressure in normal pregnancy. Med. Biol. Eng. Comput. 40(2), 241–245 (2002)CrossRef

31.

Schulz, S., Tupaika, N., Berger, S., Haueisen, J., Bär, K.-J., Voss, A.: Cardiovascular coupling analysis with high-resolution joint symbolic dynamics in patients suffering from acute schizophrenia, 34 (2013)

32.

Schumann, A., Schulz, S., Voss, A., Scharbrodt, S., Baumert, M., Bär, K.-J.: Baroreflex Coupling Assessed by Cross-Compression Entropy. Front. Physiol. 8, 282 (2017)

33.

Pikovsky, A., Rosenblum, M., Kurths, J., Kurths, J.: Synchronization: a universal concept in nonlinear sciences. vol. 12. Cambridge university press (2003)

34.

Stefanovska, A., Haken, H., McClintock, P.V.E., Hožič, M., Bajrović, F., Ribarič, S.: Reversible transitions between synchronization states of the cardiorespiratory system. Phys. Rev. Lett. 85(22), 4831 (2000)CrossRef

35.

Bartsch, R., Kantelhardt, J.W., Penzel, T., Havlin, S.: Experimental evidence for phase synchronization transitions in the human cardiorespiratory system. Phys. Rev. Lett. 98(5), 54102 (2007)CrossRef

36.

Toledo, E., Akselrod, S., Pinhas, I., Aravot, D.: Does synchronization reflect a true interaction in the cardiorespiratory system? Med. Eng. Phys. 24(1), 45–52 (2002)CrossRef

37.

Wu, M.-C., Hu, C.-K.: Empirical mode decomposition and synchrogram approach to cardiorespiratory synchronization. Phys. Rev. E 73(5), 51917 (2006)CrossRef

38.

Cysarz, D., Büssing, A.: Cardiorespiratory synchronization during Zen meditation. Eur. J. Appl. Physiol. 95(1), 88–95 (2005)CrossRef

39.

Samarbakhsh, L.: Web search algorithms and PageRank (2008)

40.

Alagoz, O., Maillart, L.M., Schaefer, A.J., Roberts, M.S.: The optimal timing of living-donor liver transplantation. Manage. Sci. 50(10), 1420–1430 (2004)CrossRef

41.

Maillart, L.M., Ivy, J.S., Ransom, S., Diehl, K.: Assessing dynamic breast cancer screening policies. Oper. Res. 56(6), 1411–1427 (2008)CrossRef

42.

Faissol, D.M., Griffin, P.M., Swann, J.L.: Timing of testing and treatment of hepatitis C and other diseases. In: Proceedings, p. 11 (2007)

Title: Cardiorespiratory Coupling: A Review of the Analysis Methods
Authors: V. Tonu
V. Vovc
N. Enache
Publisher: Springer International Publishing
Book: 4th International Conference on Nanotechnologies and Biomedical Engineering
Print ISBN: 978-3-030-31865-9

Electronic ISBN: 978-3-030-31866-6

Copyright Year: 2020
DOI: https://doi.org/10.1007/978-3-030-31866-6_84