昼夜节律下心率变异性信号的熵信息和谱特征

生理系统产生的复杂波动信号能够反映其潜在的动力学特征.采用基本尺度熵和功率谱的方法分析24 h心率变异性信号.结果表明,心脏系统昼夜节律下生理和病理的变化伴随着变化的基本尺度熵和功率谱分布,但是对于近似熵,其变化却不明显;同时发现,基本尺度熵的变化能够反映相应的自主神经调控的变化,由于充血性心力衰竭患者迷走神经的调控被抑制,交感神经的调控占优势,所以数据中会出现更多变化的矢量模式组合,因此心力衰竭患者心率变异性信号的熵值较高;在夜间睡眠状态时,由于迷走神经的调控增强,交感神经的调控减少,所以健康人和心力衰竭患者的基本尺度熵都比白天清醒状态时产生了下降趋势.     

对称双势阱玻色-爱因斯坦凝聚系统在周期驱动下的动力学相变及其量子纠缠熵表示

研究了在对称双势阱玻色-爱因斯坦凝聚体系粒子间相互作用项上外加周期调制而引起的系统动力学相变,特别地研究了该系统通向混沌的相变过程.发现在一定驱动参数下,当外加调制频率与系统固有频率达到共振时,相平面会出现不稳定性现象,即混沌.在混沌区域,粒子在各量子态随机分布,平均布居数差在零附近波动.特别地,研究表明,混沌现象的出现可以用量子纠缠熵来表征,混沌现象出现时,两种平均纠缠熵都趋于它们的最大值. 关键词： 玻色-爱因斯坦凝聚 双势阱 混沌 纠缠熵     

基于多尺度熵的Duffing混沌系统阈值确定方法

熵是热力学中表征物质状态的参量之一,是体系混乱程度的度量.一个信号的熵可以用来表示信号的复杂度. Duffing混沌系统从临界混沌状态向大尺度周期状态跃变的阈值是混沌系统分析的一个重要参数,它的求解方法是混沌理论目前亟待解决的问题之一.然而传统的实验分析法或者定量分析法存在一定的局限性.本文在研究中发现,系统处于混沌态和周期态时输出的多尺度熵值存在较大差异,且当系统进入周期态后多尺度熵值趋于平稳,基于这一现象结合遗传算法提出了基于多尺度熵的Duffing混沌系统阈值确定方法.利用该方法对正弦信号和方波信号的检测系统跃变阈值进行了计算,结果表明该方法快速准确且计算简单.     

对称双势阱玻色-爱因斯坦凝聚系统在周期驱动下的动力学相变及其量子纠缠熵表示

研究了在对称双势阱玻色-爱因斯坦凝聚体系粒子间相互作用项上外加周期调制而引起的系统动力学相变，特别地研究了该系统通向混沌的相变过程.发现在一定驱动参数下，当外加调制频率与系统固有频率达到共振时，相平面会出现不稳定性现象，即混沌.在混沌区域，粒子在各量子态随机分布，平均布居数差在零附近波动.特别地，研究表明，混沌现象的出现可以用量子纠缠熵来表征，混沌现象出现时，两种平均纠缠熵都趋于它们的最大值.     

混沌信号在光纤传输过程中的非线性演化

对光纤混沌传输理论及混沌信号与光纤传输媒介相互作用的物理机制进行了理论研究. 通过耦合激光混沌系统和光纤传输信道，提出光纤混沌信号传输的非线性演化物理模型. 着重分析光纤自相位调制对激光混沌信号传输与演化的作用. 结果表明：自相位调制不影响混沌信号脉冲的形状，但能产生非线性相移使混沌信号频谱展宽；自相位调制不影响混沌信号脉冲的功率分布和场强分布，但能影响混沌信号脉冲的功率频谱分布，影响混沌信号光场以及慢变场的变化. 提出混沌信号在光纤传输中的非线性演化频率啁啾和形式，数值模拟了混沌信号在光纤传输过程中的相位、频谱、场以及场的慢变部分的相空间等演化形式和特点. 关键词： 混沌 光纤 传输 演化     

反馈强度调制增强混沌光通信的保密性

注入锁定式光混沌同步通信系统对收发机的参数失配有较大的容忍度,这在一定程度上降低了信息的安全性.提出采用反馈强度的调制来提高系统的保密性.数值模拟分析了调制前后系统提取信号质量的变化,以及收发机调制的速率失谐、延时对提取信号质量的影响.研究发现：仅在发射机增加反馈强度调制后,同步性恶化、误码率增大两个数量级,无法提取信号;而在接收机引入相同的调制后,系统同步性及误码率得到恢复.此外,收发机的反馈强度调制速率失谐和延时范围分别在±5 MHz和±0.1倍调制周期时,信息提取质量较高.反馈强度调制能够有效地增强传统混沌通信系统的保密性. 关键词： 反馈强度 调制 混沌通信 保密     

应用多尺度化的基本尺度熵分析心率变异性

本文采用多尺度化的基本尺度熵方法,针对心率变异性信号进行了分析,研究发现多尺度化的基本尺度熵可以区分不同生理病理信号,包括健康人、充血性心力衰竭患者和房颤心律失常患者的心率变异性信号,以及健康人白天黑夜的心率变异性信号.通过对健康人代理数据的分析,发现房颤心律失常患者与代理数据的熵值趋势相似,研究结果表明房颤心律失常患者的心率变异性信号更多的是反映生理信号的线性特征,而对环境变化不能很好的进行自我调节. 关键词： 多尺度化的基本尺度熵 心率变异性 充血性心力衰竭 房颤心律失常     

功能磁共振成像的基本尺度熵分析

人体大脑活动的复杂度随年龄变化而变化, 并且和性别有一定的联系, 通过对功能磁共振成像复杂度的分析有助于发现人脑活动和性别年龄之间关系的规律. 本文提出需要根据年龄段的变化对基本尺度熵的参数做适当的调整, 以便获得良好的信号区分效果. 本文研究了人脑活动和性别年龄之间存在的关系. 结果证明, 同龄男女的基本尺度熵值存在一定的差异, 并且随年龄段的不同发生相应的变化, 另外基本尺度熵中的参数在数据分析中也随年龄变化存在一定规律的变化. 通过对fMRI数据的分析表明, 基本尺度熵能够有效地区分不同人群fMRI数据特征, 为进一步信号复杂度分析提供方便. 关键词： 功能磁共振成像 基本尺度熵 复杂度     

Bell态原子与双模纠缠相干光场相互作用的场熵演化特性

运用全量子理论研究了初始处于Bell态(对称迭加态或反对称态)的两原子与双模纠缠相干光场相互作用系统中场熵的演化特性. 分析了光场强度、光场纠缠度及原子间相互作用强度对场熵演化特性的影响. 结果表明：原子初态处于反对称态时,场熵始终为零;原子初态处在对称迭加态时,增大光场强度场熵的时间演化曲线逐渐变成较规则的振荡曲线,原子间的相互作用强度对双原子间纠缠度有显著的非线性调制作用.     

Bell态原子与双模纠缠相干光场相互作用的场熵演化特性

运用全量子理论研究了初始处于Bell态(对称迭加态或反对称态)的两原子与双模纠缠相干光场相互作用系统中场熵的演化特性. 分析了光场强度、光场纠缠度及原子间相互作用强度对场熵演化特性的影响. 结果表明：原子初态处于反对称态时,场熵始终为零;原子初态处在对称迭加态时,增大光场强度场熵的时间演化曲线逐渐变成较规则的振荡曲线,原子间的相互作用强度对双原子间纠缠度有显著的非线性调制作用.     

Dynamical complexity changes during two forms of meditation

Detection of dynamical complexity changes in natural and man-made systems has deep scientific and practical meaning. We use the base-scale entropy method to analyze dynamical complexity changes for heart rate variability (HRV) series during specific traditional forms of Chinese Chi and Kundalini Yoga meditation techniques in healthy young adults. The results show that dynamical complexity decreases in meditation states for two forms of meditation. Meanwhile, we detected changes in probability distribution of m-words during meditation and explained this changes using probability distribution of sine function. The base-scale entropy method may be used on a wider range of physiologic signals.     

Detecting dynamical complexity changes in time series using the base-scale entropy

Timely detection of dynamical complexity changes in natural and man-made systems has deep scientific and practical meanings. We introduce a complexity measure for time series： the base-scale entropy. The definition directly applies to arbitrary real-word data. We illustrate our method on a practical speech signal and in a theoretical chaotic system. The results show that the simple and easily calculated measure of base-scale entropy can be effectively used to detect qualitative and quantitative dynamical changes.     

玻色-爱因斯坦凝聚中的混沌反控制

提出一种实现玻色-爱因斯坦凝聚中的混沌反控制方法——周期信号驱动法.数值模拟结果表明,用小的周期信号控制系统,采用恰当的调制相位和强度,只要满足系统的最大Lyapunov指数大于零即可实现不同的混沌轨道重构.调制相位在混沌轨道重构中起了很重要的作用. 关键词： 玻色-爱因斯坦凝聚 混沌反控制 小周期信号 Lyapunov指数     

Multifractal Analysis of Human Heartbeat in Sleep

We study the dynamical properties of heart rate variability （HRV） in sleep by analysing the scaling behaviour with the multifractal detrended fluctuation analysis method. It is well known that heart rate is regulated by the interaction of two branches of the autonomic nervous system： the parasympathetic and sympathetic nervous systems. By investigating the multifractal properties of light, deep, rapid-eye-movement （REM） sleep and wake stages, we firstly find an increasing multifractal behaviour during REM sleep which may be caused by augmented sympathetic activities relative to non-REM sleep. In addition, the investigation of long-range correlations of HRV in sleep with second order detrended fluctuation analysis presents irregular phenomena. These findings may be helpful to understand the underlying regulating mechanism of heart rate by autonomic nervous system during wake-sleep transitions.     

Investigation of determinism in heart rate variability

The article searches for the possible presence of determinism in heart rate variability (HRV) signals by using a new approach based on NARMA (nonlinear autoregressive moving average) modeling and free-run prediction. Thirty-three 256-point HRV time series obtained from Wistar rats submitted to different autonomic blockade protocols are considered, and a collection of surrogate data sets are generated from each one of them. These surrogate sequences are assumed to be nondeterministic and therefore they may not be predictable. The original HRV time series and related surrogates are submitted to NARMA modeling and prediction. Special attention has been paid to the problem of stationarity. The results consistently show that the surrogate data sets cannot be predicted better than the trivial predictor-the mean-while most of the HRV control sequences are predictable to a certain degree. This suggests that the normal HRV signals have a deterministic signature. The HRV time series derived from the autonomic blockade segments of the experimental protocols do not show the same predictability performance, albeit the physiological interpretation is not obvious. These results have important implications to the methodology of HRV analysis, indicating that techniques from nonlinear dynamics and deterministic chaos may be applied to elicit more information about the autonomic modulation of the cardiovascular activity. (c) 2000 American Institute of Physics.     

Classification of physiologic and synthetic heart rate variability series using base-scale entropy

The base-scale entropy method was used as a measure to classify physiologic and synthetic heart rate variability series. This method enables analyzing very short, non-stationary, and noisy data. We used it to analyze short-term heart rate variability series. The results show that our method can effectively detect the complex dissimilarity of physiologic time series in different physiologic/pathologic states. We then applied it to the CinC 2002 test datasets. Using the base-scale entropy, we correctly classified 43 of 46 (93%) time series. In combination with time domain analysis, we correctly classified all time series.     

心率变异性分析在新生儿疼痛检测中的应用

为了研究疼痛暴露对新生儿自主神经系统的影响,并建立基于心率变异性(heart rate variability,HRV)指标的新生儿疼痛检测模型,采用时域、频域和非线性方法对40名新生儿疼痛暴露前后的心电数据进行短时HRV分析,Wilcoxon符号秩检验用于统计分析,支持向量机(support vector machine,SVM)用于建立检测模型.结果表明,RR间期均值a RR、低频段功率LF、高频段功率HF等3个线性指标和近似熵Ap En、样本熵Samp En、递归率REC等9个非线性指标在疼痛前后具有统计学差异;基于a RR、相邻两个RR间期对差值大于50 ms的百分比p NN50,Ap En,关联维D2和REC等5个指标和SVM的疼痛检测模型检测正确率达到83.75%.HRV的相关指标可反映新生儿自主神经系统对疼痛暴露的应答,基于HRV指标和SVM的模型可用于新生儿疼痛检测.     

Dynamical Behaviour of the Bonhoeffer-van der Pol Model

The dynamical behaviour and the threshold phenomenon for the Bonhoeffer-van der Pol model of a nerve membrane stimulated by a constant and a periodic currents are investigated. For the constant current lo, there are two Hopf bifurcations at I₀ = I_L and I₀ = I_H, respectively. At I₀ = I_L an infinite long train of nerve impulses (threshold phenomenon) is found. For the periodic current, there are an ordinary period-dou bling to chaotic state, and a mode-locking state, as well as a reversed period-doubling from chaotic state to period-1 state. A phase diagram for the threshold phenomenon in the parameter space (I₁ and ω, amplit ude and frequency) is obtained. In our discussion we conclude that the period-n oscillations correspond to the n-shaped impulse trains, and the chaotic oscillation corresponds to the infinite-shaped impulse trains. All of these impulses of the BVP model system code the information process of the nerve fibre in neural tissue.