Significance of using a nonlinear analysis technique, the Lyapunov exponent, on the understanding of the dynamics of the cardiorespiratory system in rats

Zeren, Tamer; Özbek, Mustafa; Kutlu, Necíp; Akıllı, Mahmut

doi:10.3906/sag-1403-15

Cited by 3 publications

(2 citation statements)

References 53 publications

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“…The windowed scalogram entropy (20) and windowed scale index (23) were calculated from the windowed scalogram. We used the time series of the tracheal airflow signals including PNCG signals of a rat as the second empirical data [31] shown in figure 4(a). The PNCG is a record of the pulsatile flow of air in the trachea coincident with each heartbeat.…”

Section: Resultsmentioning

confidence: 99%

Windowed scalogram entropy: wavelet-based tool to analyze the temporal change of entropy of a time series

Akıllı

Yılmaz

2021

Eur. Phys. J. Plus

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In this paper, we propose a new entropy calculation method to observe the temporal change of the entropy of dynamical systems. The proposed entropy calculation method is based on the windowed scalogram which has been introduced recently. Therefore, we name this new method "windowed scalogram entropy". With this method, we can show the evolution of the Boltzmann-Gibbs-Shannon entropy over time using the probability distribution obtained by the normalized windowed scalogram. Before applying the method to time series with complex dynamics, we test the reliability of the method on some welldefined signals. Then, we employ seismic signals and pneumocardiogram signals to demonstrate the effectiveness of the method in the analysis of empirical data. We also compare the method with the windowed scale index and the sample entropy. It is observed that the windowed scalogram entropy is successful in analyzing the evolution of the entropy of seismic signals and pneumocardiogram signals over time. We understand that the windowed scalogram entropy can be used to observe the evolution of the entropy of nonlinear dynamical time series obtained in diverse fields.

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Section: Resultsmentioning

confidence: 99%

Windowed scalogram entropy: wavelet-based tool to analyze the temporal change of entropy of a time series

Akıllı

Yılmaz

2021

Eur. Phys. J. Plus

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“…Pneumocardiography signals (PNCG), which consist of both lung and heart motions, are measured via induced pressure/flow pulses in the airway are the subject of the present paper. The PNCG were considered to be interesting time series to study nonlinear properties of the cardiorespiratory system of living rats [13,14], but no comparative nonlinear analysis has been performed previously: the studies mentioned above focused on the reconstructing phase space and Lyapunov exponents of PNCG signals [13,14].…”

Section: Introductionmentioning

confidence: 99%

Application of the nonlinear methods in pneumocardiogram signals

Yılmaz

Akıllı²,

Özbek

et al. 2020

J Biol Phys

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In this work, the pneumocardiogram signals of nine rats were analysed by scale index, Boltzmann Gibbs entropy and maximum Lyapunov exponents. The scale index method, based on wavelet transform, was proposed for determining the degree of aperiodicity and chaos. It means that the scale index parameter is close to zero when the signal is periodic and has a value between zero and one when the signal is aperiodic. A new entropy calculation method by normalized inner scalogram was suggested very recently. In this work, we also used this method for the first time in an empirical data. We compared the both methods with maximum Lyapunov exponents and observed that using together the scale index and the entropy calculation method by normalized inner scalogram increases the reliability of the pneumocardiogram signal analysis. Thus, the analysis of the pneumocardiogram signals by those methods enables to compare periodical and/or nonlinear aspects for further understanding of dynamics of cardiorespiratory system.

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Nonlinear feedback coupling in Hindmarsh–Rose neurons

Thottil¹,

Ignatius²

2016

Nonlinear Dyn

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Significance of using a nonlinear analysis technique, the Lyapunov exponent, on the understanding of the dynamics of the cardiorespiratory system in rats

Abstract: A method was proposed to determine the diagnostic and prognostic values of the cardiorespiratory system of rats using the arrangement of the PNCG and Lyapunov exponents, which may be monitored as vitality indicators.

Cited by 3 publications

References 53 publications

Windowed scalogram entropy: wavelet-based tool to analyze the temporal change of entropy of a time series

Windowed scalogram entropy: wavelet-based tool to analyze the temporal change of entropy of a time series

Application of the nonlinear methods in pneumocardiogram signals

Nonlinear feedback coupling in Hindmarsh–Rose neurons

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