Cross-correlation of heartbeat and respiration rhythms

The cross-correlation function between respiration and heart beat interval series shows that during metronomized breathing¹ the heart beat follows the respiration more closely than during spontaneous breathing. We reproduced the heart beat interval modulations during metronomized breathing using a biophysical model of the sinoatrial node excited by an input signal formed by the recorded respiration. In the case of spontaneous breathing, a good agreement with the experimental data was obtained only by using an input signal formed by the sum of the recorded respiration and a realization of correlated noise.     

Enhanced soliton transport in quasiperiodic lattices with introduced aperiodicity

We study linear transmission and nonlinear soliton transport through quasiperiodic structures, where the lattice profiles are described by multiple modulation frequencies. We show that resonant scattering at mixed-frequency resonances limits transmission efficiency of localized wave packets, leading to radiation and possible trapping of solitons. We obtain an explicit analytical expression for optimal quasiperiodic lattice profiles, where additional aperiodic modulations suppress mixed-frequency resonances, resulting in dramatic enhancement of soliton mobility. Our results can be applied to the design of photonic waveguide structures, and arrays of magnetic micro-traps for atomic Bose-Einstein condensates.     

ac-Conductivity of aperiodic chains re-examined

ac-Conductivity of infinite quasiperiodic chanins have been calculated using the Miller-Abrahams equations and a real space decimation technique. Our approach deals with the infinite lattice directly, instead of calculating the conductivity for periodic repetitions of long quasiperiodic segments, as has been done recently. We point out an interesting observation that, some aperiodic chains show the same analytical behaviour in the low frequency ac-conductivity as an ordered chain, whereas, some others behave in a totally different way. We explain this observation from a renormalization group point of view.     

Dynamic analysis of heartbeat rate signals of epileptics using multidimensional phase space reconstruction approach

The heartbeat rate signal provides an invaluable means of assessing the sympathetic-parasympathetic balance of the human autonomic nervous system and thus represents an ideal diagnostic mechanism for detecting a variety of disorders such as epilepsy, cardiac disease and so forth. The current study analyses the dynamics of the heartbeat rate signal of known epilepsy sufferers in order to obtain a detailed understanding of the heart rate pattern during a seizure event. In the proposed approach, the ECG signals are converted into heartbeat rate signals and the embedology theorem is then used to construct the corresponding multidimensional phase space. The dynamics of the heartbeat rate signal are then analyzed before, during and after an epileptic seizure by examining the maximum Lyapunov exponent and the correlation dimension of the attractors in the reconstructed phase space. In general, the results reveal that the heartbeat rate signal transits from an aperiodic, highly-complex behaviour before an epileptic seizure to a low dimensional chaotic motion during the seizure event. Following the seizure, the signal trajectories return to a highly-complex state, and the complex signal patterns associated with normal physiological conditions reappear.     

Marked signal improvement by stochastic resonance for aperiodic signals in the double-well system

On the basis of our mixed-signal simulations we report significant stochastic resonance induced input-output signal improvement in the double-well system for aperiodic input types. We used a pulse train with randomised pulse locations and a band-limited noise with low cut-off frequency as input signals, and applied a cross-spectral measure to quantify their noise content. We also supplemented our examinations with simulations in the Schmitt trigger to show that the signal improvement we obtained is not a result of a potential filtering effect due to the limited response time of the double-well dynamics.     

运动后人体心肺节律同步关系及信号的耦合方向

研究运动后青年心肺系统的耦合关系.通过提取在校学生运动后的心跳和呼吸信号,采用经验模态分解的方法对信号进行滤波,分析了心肺信号的相同步行为和心肺节律间耦合作用的相对强弱关系.结果表明,人体在运动后仍然存在心肺系统节律同步现象.这种同步比例不仅因人而异,而且因时而异.由传递熵的计算结果得知,呼吸对于心跳的耦合作用相对较大.     

Stochastic resonance in the FitzHugh-Nagumo model from a dynamic mutual information point of view

Stochastic resonance(SR) in a FitzHugh-Nagumo neuron model is investigated based on a dynamic mutual information (DMI) between the input and the corresponding output signals. The DMI is expressed in terms of the (cross)power spectra of the input and output time series. Both stochastic-periodic and aperiodic SR are treated based on the DMI and our results are in good accord with the SR measured by the signal to noise ratio(SNR) for the case of the stochastic-periodic input and the power norm for the case of the aperiodic input.     

Analysis of heartbeat asymmetry based on multi-scale time irreversibility test

We investigate the asymmetry of heart rate control system and suggest a simple index to quantify this asymmetry by performing high-dimensional time irreversibility tests to heartbeat interval time series over multiple scales. The results provide strong evidence to the concept that the asymmetry is an intrinsic property of heart rate control system. As a simple and visual method, it is proved to be effective in classifying physiologic and synthetic subjects while the maximum scale is selected within a proper range, and also provides a new way to analyze the time irreversibility for other high-dimensional systems.     

分数阶双稳系统中的非周期振动共振

在受二进制非周期信号和周期方波信号激励的分数阶双稳系统中,研究了非周期振动共振问题,用于微弱非周期信号的检测和增强.当非周期信号脉宽较大时,系统为小参数,通过调节周期方波信号的幅值,能够实现非周期振动共振.当非周期信号脉宽较小时,分别通过变尺度法和二次采样法实现了非周期振动共振.使用变尺度法,得到的大参数等价系统能够匹配任意小的非周期信号脉宽,其中变尺度系数是该方法在使用过程中需要选择的关键参数.使用二次采样法,二次采样后得到的非周期信号具有较大的脉宽,能够匹配原先的小参数系统,其中二次采样频率比是该方法使用过程中的关键参数.这两种方法虽然实现非周期振动共振的物理过程不同,但能够达到相同的效果.系统阶数对振动共振产生影响,随着阶数的增大,发生最佳振动共振时所需要的辅助信号幅值变大,同时系统输出的最佳时间序列与输入非周期信号之间的相似性增强.     

Q-Dependent Susceptibilities in Ferromagnetic Quasiperiodic Z-Invariant Ising Models

We study the q-dependent susceptibility χ(q) of a series of quasiperiodic Ising models on the square lattice. Several different kinds of aperiodic sequences of couplings are studied, including the Fibonacci and silver-mean sequences. Some identities and theorems are generalized and simpler derivations are presented. We find that the q-dependent susceptibilities are periodic, with the commensurate peaks of χ(q) located at the same positions as for the regular Ising models. Hence, incommensurate everywhere-dense peaks can only occur in cases with mixed ferromagnetic–antiferromagnetic interactions or if the underlying lattice is aperiodic. For mixed-interaction models the positions of the peaks depend strongly on the aperiodic sequence chosen. Supported in part by NSF Grant No. PHY 01-00.     

Enhancing aperiodic stochastic resonance through noise modulation

We show that the conventional stochastic resonance (SR) effect for aperiodic signals in a model neuron can be enhanced by modulating the intensity of the input noise (which could be introduced artificially in bioengineering applications) with either the input signal or the unit's output rate signal. We analyze SR enhancement theoretically and numerically. We discuss how this work provides the theoretical foundation for the development of an optimal noise-based technique for enhancing sensory function. (c) 1998 American Institute of Physics.     

Multifractal analysis of heartbeat dynamics during meditation training

We investigate the multifractality of heartbeat dynamics during Chinese CHI meditation in healthy young adults. The results show that the range of multifractal singularity spectrum of heartbeat interval time series during meditation is significantly narrower than those in the pre-meditation state of the same subject, which indicates that during meditation the heartbeat becomes regular and the degree of multifractality decreases.     

Low-energy properties of aperiodic quantum spin chains

We investigate the low-energy properties of antiferromagnetic quantum XXZ spin chains with couplings following two-letter aperiodic sequences, by an adaptation of the Ma-Dasgupta-Hu renormalization-group method. For a given aperiodic sequence, we argue that, in the easy-plane anisotropy regime, intermediate between the XX and Heisenberg limits, the general scaling form of the thermodynamic properties is essentially given by the exactly known XX behavior, providing a classification of the effects of aperiodicity on XXZ chains. As representative illustrations, we present analytical and numerical results for the low-temperature thermodynamics and the ground-state correlations for couplings following the Fibonacci quasiperiodic structure and a binary Rudin-Shapiro sequence, whose geometrical fluctuations are similar to those induced by randomness.     

Sources of functional magnetic resonance imaging signal fluctuations in the human brain at rest: a 7 T study

Signal fluctuations in functional magnetic resonance imaging (fMRI) can result from a number of sources that may have a neuronal, physiologic or instrumental origin. To determine the relative contribution of these sources, we recorded physiological (respiration and cardiac) signals simultaneously with fMRI in human volunteers at rest with their eyes closed. State-of-the-art technology was used including high magnetic field (7 T), a multichannel detector array and high-resolution (3 mm³) echo-planar imaging. We investigated the relative contribution of thermal noise and other sources of variance to the observed fMRI signal fluctuations both in the visual cortex and in the whole brain gray matter. The following sources of variance were evaluated separately: low-frequency drifts due to scanner instability, effects correlated with respiratory and cardiac cycles, effects due to variability in the respiratory flow rate and cardiac rate, and other sources, tentatively attributed to spontaneous neuronal activity. We found that low-frequency drifts are the most significant source of fMRI signal fluctuations (3.0% signal change in the visual cortex, TE=32 ms), followed by spontaneous neuronal activity (2.9%), thermal noise (2.1%), effects due to variability in physiological rates (respiration 0.9%, heartbeat 0.9%), and correlated with physiological cycles (0.6%). We suggest the selection and use of four lagged physiological noise regressors as an effective model to explain the variance related to fluctuations in the rates of respiration volume change and cardiac pulsation. Our results also indicate that, compared to the whole brain gray matter, the visual cortex has higher sensitivity to changes in both the rate of respiration and the spontaneous resting-state activity. Under the conditions of this study, spontaneous neuronal activity is one of the major contributors to the measured fMRI signal fluctuations, increasing almost twofold relative to earlier experiments under similar conditions at 3 T.     

Chaotic Oscillations in a Nonlinear Lumped-Parameter Transmission Line

We present the results of numerical simulation of the complex dynamics of a nonlinear radio-technical line having reflections at the boundaries and excited by an external harmonic signal. It is shown that, with increase in the amplitude of the input signal, periodic oscillations at the external-forcing frequency become unstable and are changed to more complex regimes, either quasiperiodic or chaotic. The main scenarios of transition to chaos are studied. The influence of the modulation instability and soliton formation on the complex dynamics is discussed.     

PCIe接口的BAC时统节点设计

针对BAC时统节点在PCIe计算机系统中的应用,基于新型线性隔离和PCIe端点硬核应用和BAC码转换解析,实现了一种BAC时统节点设计。实现了该节点的总体电路设计,同时实现了BAC输入信号的线性隔离电路、迟滞比较输出BAC信号采样点电路、BAC信号的A/D转换采集电路、ALTERA FPGA的FIFO和PCIe端点硬核应用设计。基于FPGA实现的PCIe接口、FIFO和控制逻辑计以及实现的线性隔离,在简化节点设计的同时,也大大提高了适用性。     

Experimental evidence for phase synchronization transitions in the human cardiorespiratory system

Transitions in the dynamics of complex systems can be characterized by changes in the synchronization behavior of their components. Taking the human cardiorespiratory system as an example and using an automated procedure for screening the synchrograms of 112 healthy subjects we study the frequency and the distribution of synchronization episodes under different physiological conditions that occur during sleep. We find that phase synchronization between heartbeat and breathing is significantly enhanced during non-rapid-eye-movement (non-REM) sleep (deep sleep and light sleep) and reduced during REM sleep. Our results suggest that the synchronization is mainly due to a weak influence of the breathing oscillator upon the heartbeat oscillator, which is disturbed in the presence of long-term correlated noise, superimposed by the activity of higher brain regions during REM sleep.     

Phase transition in aperiodic spin chains

The quantum-mechanical transition in the ground state of some aperiodic spin chains is considered. Exact expressions for the energy gap and the dispersion relation of low-energy excitations close to the critical point are derived. Applications of these results to the study of particular quasiperiodic and random models are discussed.     

Phonon spectra of a Fibonacci chain

Based on more realistic physics we study the phonon spectra of the Fibonacci chain by taking into account a nonlinear resistance. It is found that the nonlinear force should be very weak and consequently, the continuity, range and gaps of the phonon spectra would be still controlled dominantly by the relative strength of spring constants and chain length. It means that even if no additional nonlinear resistance was taken into account, the conventional results of phonon spectra are exactly correct. On the other hand, in the framework of a conventional model we investigated the relationship between the biggest gaps of phonon spectra and defects of Fibonacci-like aperiodic chains. By means of numerical calculations one can obtain quantitatively the maximum of the length of a one-dimensional aperiodic chain sensitive to boundaries. This method would be useful for the calculation of quasiperiodic and aperiodic lattices.     

Alteration in scaling behavior of short-term heartbeat time series for professional shooting athletes from rest to exercise

Scaling analysis of heartbeat time series has emerged as a useful tool for assessing the autonomic cardiac control under various physiologic and pathologic conditions. We study the heartbeat activity and scaling behavior of heartbeat fluctuations regulated by autonomic nervous system for professional shooting athletes under two states: rest and exercise, by applying the detrended fluctuation analysis method. We focus on alteration in correlation properties of heartbeat intervals for the shooters from rest to exercise, which may have a potential value in monitoring the quality of training and evaluating the sports capacity of the athletes. The result shows that scaling exponents of short-term heart rate variability signals from the shooters get significantly larger during exercise compared with those obtained at rest. It demonstrates that during exercise stronger correlations appear in the heartbeat series of shooting athletes in order to satisfy the specific requirements for high concentration and better control on their heart beats.