Phase Transition in a Healthy Human Heart Rate

Kiyono, Ken; Struzik, Zbigniew R.; Aoyagi, Noboru; Togo, Fumiharu; Yamamoto, Yoshiharu

doi:10.1103/physrevlett.95.058101

Cited by 116 publications

(120 citation statements)

References 24 publications

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“…Furthermore, it is also found in this experiment that the phase of PP variation is delayed and that of RSA is advanced in the sitting position by changing the balance of autonomic nervous activity. Thus the respiratory-phase domain analysis used in this study is useful for elucidating the dynamic mechanisms of RSA and the sources of "complexity" in cardiovascular variability (14,17).…”

Section: Discussionmentioning

confidence: 99%

Postural-induced phase shift of respiratory sinus arrhythmia and blood pressure variations: insight from respiratory-phase domain analysis

Kotani

Takamasu²,

Jimbo³

et al. 2008

American Journal of Physiology-Heart and Circulatory Physiology

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The purpose of this study is to evaluate the multiple effects of respiration on cardiovascular variability in different postures, by analyzing respiratory sinus arrhythmia (RSA) and respiratory-related blood pressure (BP) variations for systolic BP (SBP), diastolic BP (DBP), and pulse pressure (PP) in the respiratory-phase domain. The measurements were conducted for 420 s on healthy humans in the sitting and standing positions, while the subjects were continuously monitored for heart rate and BP variability and instantaneous lung volume. The waveforms of RSA and respiratory-related BP variations were extracted as a function of the respiratory phase. In the standing position, the waveforms of the BP variations for SBP, DBP, and PP show their maxima at around the end of expiration ( rad) and the minima at around the end of inspiration (2 rad), while the waveform of RSA is delayed by ϳ0.35 rad compared with the BP waveforms. On the other hand, in the sitting position, the phase of the DBP waveform (1.69 rad) greatly and significantly (P Ͻ 0.01) differs from that in the standing position (1.20 rad). Also, the phase of PP is delayed and that of RSA is advanced in the sitting position (P Ͻ 0.01). In particular, the phase shift of the DBP waveform is sufficiently large to alter whole hemodynamic fluctuations, affecting the amplitudes of SBP and PP variations. We conclude that the postural change associated with an altered autonomic balance affects not only the amplitude of RSA, but also the phases of RSA and BP variations in a complicated manner, and the respiratory-phase domain analysis used in this study is useful for elucidating the dynamic mechanisms of RSA.heart rate variability; Hilbert transform; respiratory phase; blood pressure variability RESPIRATION HAS STRONG AND multiple effects on the cardiovascular system. The best known effect of respiration is respiratory sinus arrhythmia (RSA) (12, 13, 26), i.e., fluctuations in heart rate (HR), depending on the phases of inspiration and expiration. RSA mainly reflects the modulation of the central autonomic outflow caused by respiration-related factors, such as spontaneous oscillations of respiratory centers and pulmonary stretch receptor afferents (8), and hemodynamic factors through the baroreflex and the Bainbridge reflex (30), which interact with each other in a complicated manner (4).Blood pressure (BP) is also affected by multiple interactions of these factors. To describe quantitatively the effects of respiration on HR and BP, Saul et al. (21) constructed a model in which HR is determined by the sum of central vagal and sympathetic activity, low-pass filtered and time delayed due to peripheral neurotransmitter kinetics. Arterial BP, determining the baroreceptor activity, is influenced by HR with some (mechanical) time delays. Then they incorporated the respiratory effects on HR and BP in two ways. First, instantaneous lung volume (ILV) has a (respiration-related) inhibitory effect on the central nervous system, which is known to be the inhibitory effect of in...

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Section: Discussionmentioning

confidence: 99%

Postural-induced phase shift of respiratory sinus arrhythmia and blood pressure variations: insight from respiratory-phase domain analysis

Kotani

Takamasu²,

Jimbo³

et al. 2008

American Journal of Physiology-Heart and Circulatory Physiology

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“…Another type of detrended fluctuation analysis, which we will denote as Modified Detrended Fluctuation Analysis (MDFA) [38], eliminates trends similar to the DFA method. A polynomial is fitted to the profile function X(n) in each segment ν and the deviation between the profile function and the polynomial fit is calculated,X s (n) = X(n) − y (p) s (n).…”

Section: Modified Detrended Fluctuation Analysis (Mdfa)mentioning

confidence: 99%

“…• the Modified Detrended Fluctuation Analysis (MDFA) [38], which is essentially a mixture of old FA and DFA, • the continuous DFA (CDFA) technique [39,40], which is particularly intended for the detection of transitions, • the Fourier DFA [41], • a variant of DFA based on empirical mode decomposition (EMD) [42], • a variant of DFA based on singular value decomposition (SVD) [43,44], and • a variant of DFA based on high-pass filtering [45].…”

Section: Introductionmentioning

confidence: 99%

Comparison of detrending methods for fluctuation analysis

Bashan

Bartsch

Kantelhardt

et al. 2008

Physica A: Statistical Mechanics and its Applications

290

187

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We examine several recently suggested methods for the detection of long-range correlations in data series based on similar ideas as the well-established Detrended Fluctuation Analysis (DFA). In particular, we present a detailed comparison between the regular DFA and two recently suggested methods: the Centered Moving Average (CMA) Method and a Modified Detrended Fluctuation Analysis (MDFA). We find that CMA is performing equivalently as DFA in long data with weak trends and slightly superior to DFA in short data with weak trends. When comparing standard DFA to MDFA we observe that DFA performs slightly better in almost all examples we studied. We also discuss how several types of trends affect the different types of DFA. For weak trends in the data, the new methods are comparable with DFA in these respects. However, if the functional form of the trend in data is not a-priori known, DFA remains the method of choice. Only a comparison of DFA results, using different detrending polynomials, yields full recognition of the trends. A comparison with independent methods is recommended for proving long-range correlations.

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“…This makes it difficult to perform a systematic study of the problem. Thus, it is necessary to investigate the typical cooperative phenomena in nonequilibrium systems.Recently, critical behaviors have been observed experimentally [1,2,3,4,5,6,7] and numerically [8,9,10,11,12,13,14,15] in typical examples of coupled excitable elements such as neural networks and cardiac tissues. In general, such critical behaviors are classified into several groups on the basis of the exponents of divergences.…”

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confidence: 99%

Critical phenomena in globally coupled excitable elements

Ohta

Sasa

2008

Phys. Rev. E

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Critical phenomena in globally coupled excitable elements are studied by focusing on a saddlenode bifurcation at the collective level. Critical exponents that characterize divergent fluctuations of interspike intervals near the bifurcation are calculated theoretically. The calculated values appear to be in good agreement with those determined by numerical experiments. The relevance of our results to jamming transitions is also mentioned.PACS numbers: 82.40. Bj, 05.10.Gg, 89.75.Da,The understanding of cooperative phenomena in nonequilibrium systems is one of the most important problems in physics. In contrast to those in equilibrium systems, their nature essentially depends on the dynamical properties of the systems. This makes it difficult to perform a systematic study of the problem. Thus, it is necessary to investigate the typical cooperative phenomena in nonequilibrium systems.Recently, critical behaviors have been observed experimentally [1,2,3,4,5,6,7] and numerically [8,9,10,11,12,13,14,15] in typical examples of coupled excitable elements such as neural networks and cardiac tissues. In general, such critical behaviors are classified into several groups on the basis of the exponents of divergences. The classification enables the realization of a universality class for critical phenomena in coupled excitable elements. However, the broad distribution of the phenomena makes it difficult to elucidate the mechanism of the criticality. When we consider the role of the mean-field Ising model in theories of equilibrium statistical mechanics, it becomes apparent that it is necessary to develop an elegant method for theoretical analysis of a minimal model describing critical phenomena in coupled excitable elements.Thus, with this aim in mind, we analyze a previously proposed simple model for globally coupled excitable elements in this Letter [16]. In particular, we focus on a divergent behavior with respect to parameter change around a saddle-node bifurcation because the excitability of this model is related to the bifurcation. It should be noted that such transition properties have been studied for different excitable systems [2,8,10,11,14]. The main achievement of this Letter is a theoretical derivation of the critical exponents that characterize the singular behavior near a saddle-node bifurcation.Model: The excitable nature of a system is characterized by the existence of spikes in a time series. Mathematically speaking, spikes are described by trajectories near a homoclinic orbit in a differential equation. As a simple example, let us consider an ordinary differential equation ∂ t φ = ω−h sin φ for a phase variable φ ∈ [0, 2π], in which there exists the homoclinic orbit when ω = h. Then, when h is slightly larger than ω, a small perturbation for the fixed point φ * = sin −1 (ω/h) yields one spike. On the other hand, when h is slightly less than ω, the system shows an array of spikes with a long interspike interval. The qualitative change in the trajectories is an example of saddle-node bifurcation. By using thi...

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Phase Transition in a Healthy Human Heart Rate

Cited by 116 publications

References 24 publications

Postural-induced phase shift of respiratory sinus arrhythmia and blood pressure variations: insight from respiratory-phase domain analysis

Postural-induced phase shift of respiratory sinus arrhythmia and blood pressure variations: insight from respiratory-phase domain analysis

Comparison of detrending methods for fluctuation analysis

Critical phenomena in globally coupled excitable elements

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