Synchronization in noisy systems and cardiorespiratory interaction

Rosenblum, Michael G.; Kurths, Jürgen; Pikovsky, Arkady; Schäfer, Carsten; Tass, Peter A.; Abel, H

doi:10.1109/51.731320

Cited by 86 publications

(69 citation statements)

References 30 publications

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“…Analysis of phase dynamics and phase synchronization is also widely used during analysis of records of human biopotentials [71][72][73]. For that purpuse wide variety of methods were developed, including coherence function [74], synchrogram [75,76], coefficient of phase coherency [49], methods based on wavelet transform [77][78][79][80], etc.…”

Section: Analysis Of Phase Synchronization Between 01 Hz Oscillationmentioning

confidence: 99%

Method of estimation of synchronization strength between low-frequency oscillations in heart rate variability and photoplethysmographic waveform variability

Kiselev¹,

Anatoly²,

Gridnev³

et al. 2016

Russ. Open Med. J.

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Abstract:This paper describes in detail a new method proposed by authors for quantitative estimation of the strength of synchronization between the low-frequency oscillations (with the main frequency of about 0.1 Hz) in the heart rate variability (HRV) and photoplethysmogram (PPG). Calculation of index value is followed by statistical significance control. The proposed method is applied for the analysis of 1056 pairs of HRV and PPG signals obtained from patients having different clinical status. Methodological recommendations are developed for method application in clinical studies. Keywords: low-frequency oscillations, heart rate variability, photoplethysmogram, baroreflexCite as Kiselev AR, Karavaev AS, Gridnev VI, Prokhorov MD, Ponomarenko VI, Borovkova EI, Shvartz VA, Ishbulatov YM, Posnenkova OM, Bezruchko BP. Method of estimation of synchronization strength between low-frequency oscillations in heart rate variability and photoplethysmographic waveform variability.

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Section: Analysis Of Phase Synchronization Between 01 Hz Oscillationmentioning

confidence: 99%

Method of estimation of synchronization strength between low-frequency oscillations in heart rate variability and photoplethysmographic waveform variability

Kiselev¹,

Anatoly²,

Gridnev³

et al. 2016

Russ. Open Med. J.

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“…Phase synchronisation analysis describes the strength of interaction between the intrinsic phases (W) of two weakly-coupled, nonstationary, nonlinear chaotic oscillators [26,27]. Two oscillators are said to be 'synchronised' or 'phase-locked' when the difference in their phases remain constant over a given length of time [22,23,28,29].…”

Section: Phase Synchronisation and Dynamic Cerebral Autoregulationmentioning

confidence: 99%

Dynamic Cerebral Autoregulation Is Acutely Impaired During Maximal Apnoea In Trained Divers

Cross¹,

Kavanagh²,

Brešković³

et al. 2014

Medicine & Science in Sports & Exercise

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Aims: To examine whether dynamic cerebral autoregulation is acutely impaired during maximal voluntary apnoea in trained divers.Methods: Mean arterial pressure (MAP), cerebral blood flow-velocity (CBFV) and end-tidal partial pressures of O 2 and CO 2 (PETO 2 and PETCO 2 ) were measured in eleven trained, male apnoea divers (2862 yr; 18262 cm, 7667 kg) during maximal ''dry'' breath holding. Dynamic cerebral autoregulation was assessed by determining the strength of phase synchronisation between MAP and CBFV during maximal apnoea.Results: The strength of phase synchronisation between MAP and CBFV increased from rest until the end of maximal voluntary apnoea (P,0.05), suggesting that dynamic cerebral autoregulation had weakened by the apnoea breakpoint. The magnitude of impairment in dynamic cerebral autoregulation was strongly, and positively related to the rise in PETCO 2 observed during maximal breath holding (R 2 = 0.67, P,0.05). Interestingly, the impairment in dynamic cerebral autoregulation was not related to the fall in PETO 2 induced by apnoea (R 2 = 0.01, P = 0.75).Conclusions: This study is the first to report that dynamic cerebral autoregulation is acutely impaired in trained divers performing maximal voluntary apnoea. Furthermore, our data suggest that the impaired autoregulatory response is related to the change in PETCO 2 , but not PETO 2 , during maximal apnoea in trained divers.

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“…1,4 However, as these biological signals are inherently nonlinear, nonstationary, and contain superimposed noise, the techniques mentioned above often prove to be inadequate for characterizing their complex dynamics. 23,39 Dynamic relationships between heart rate and respiratory rate were assessed by various approaches, and consequently there is still substantial terminological and conceptual indifference in this field. For this reason, we consider it important to clearly define terms used in the current work.…”

Section: Introductionmentioning

confidence: 99%

Quantification of Cardiorespiratory Interactions Based on Joint Symbolic Dynamics

et al. 2011

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Abstract-Cardiac and respiratory rhythms are highly nonlinear and nonstationary. As a result traditional time-domain techniques are often inadequate to characterize their complex dynamics. In this article, we introduce a novel technique to investigate the interactions between R-R intervals and respiratory phases based on their joint symbolic dynamics. To evaluate the technique, electrocardiograms (ECG) and respiratory signals were recorded in 13 healthy subjects in different body postures during spontaneous and controlled breathing. Herein, the R-R time series were extracted from ECG and respiratory phases were obtained from abdomen impedance belts using the Hilbert transform. Both time series were transformed into ternary symbol vectors based on the changes between two successive R-R intervals or respiratory phases. Subsequently, words of different symbol lengths were formed and the correspondence between the two series of words was determined to quantify the interaction between cardiac and respiratory cycles. To validate our results, respiratory sinus arrhythmia (RSA) was further studied using the phase-averaged characterization of the RSA pattern. The percentage of similarity of the sequence of symbols, between the respective words of the two series determined by joint symbolic dynamics, was significantly reduced in the upright position compared to the supine position (26.4 ± 4.7 vs. 20.5 ± 5.4%, p < 0.01). Similarly, RSA was also reduced during upright posture, but the difference was less significant (0.11 ± 0.02 vs. 0.08 ± 0.01 s, p < 0.05). In conclusion, joint symbolic dynamics provides a new efficient technique for the analysis of cardiorespiratory interaction that is highly sensitive to the effects of orthostatic challenge.

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Synchronization in noisy systems and cardiorespiratory interaction

Cited by 86 publications

References 30 publications

Method of estimation of synchronization strength between low-frequency oscillations in heart rate variability and photoplethysmographic waveform variability

Method of estimation of synchronization strength between low-frequency oscillations in heart rate variability and photoplethysmographic waveform variability

Dynamic Cerebral Autoregulation Is Acutely Impaired During Maximal Apnoea In Trained Divers

Quantification of Cardiorespiratory Interactions Based on Joint Symbolic Dynamics

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