改进G-P算法与睡眠脑电的关联维

脑电的非线性参数能有效表达大脑的不同生理状态,不同睡眠期脑电的关联维数不同.但用G- P算法求关联维数存在抗干扰能力较差、可靠性不稳定、运算量巨大等缺点.先对相空间进行奇异谱分析,进而对原始相空间进行旋转,使其成为正交的等效空间,然后再使用G- P算法.改进后的算法能有效地抑制噪声干扰,降低相空间规模,减少运算复杂性,在睡眠脑电的关联维数计算上效果良好.     

EEG非线性特征参数的研究

脑电图(EEG)记录了神经元群的电活动,为脑信息处理特征的研究提供重要的信息.基于相空间重构思想的时间序列分维算法(G-P算法)提取EEG信号的特征参数,讨论了G-P算法的三个重要参数,即无标度域、嵌入维数和延时的确定规则,记录大脑在不同状态下的EEG信号并计算其关联维数.实验结果表明,EEG关联维数可以有效地区分大脑不同状态的特征,关联维数可以作为脑信息处理的非线性特征参数.     

利用多导脑电序列的非线性分析测评精神负荷

精神负荷的研究对于改善工作环境和提高工作效率有着重要的意义，脑电、心电、呼吸等生理参数分析可以作为测评精神负荷的重要手段。本研究针对多导脑电提出了一种基于时间延迟和序列相关性的多导信号相空间重构的非线性动力学分析方法。对仿真数据的研究表明这种重构方法在信号的确定性和相关维数计算中具有良好的性能。试验脑电数据的关联维数计算和精神负荷水平的变化具有很强的一致性。结果表明该方法适用于多导脑电序列的非线性分析并可作为测评精神负荷的重要依据。     

脑电混沌维数复杂度连续检测方法的研究

一些研究表明,脑电信号具有低维的混沌动力学特性,脑电的维数则反映脑信息处理过程中的神经元集群的活动状态,是研究脑电信号的重要非线性参数.在Grassberger-Procaccia计算关联维数算法的基础上,通过改进计算关联积分的过程,提出一种适合于移动重叠窗口的维数复杂度连续检测方法.另外,还对关联积分线性区间选择上做了改进,使得所求得的参数在严格意义上为维数复杂度.数值仿真验证了该方法的正确性,并在此基础上对视觉输入变化的EEG信号进行动态数据分析,结果显示睁眼时脑电的复杂度明显高于闭眼时脑电的复杂度.所提出的维数复杂度计算方法减少了数据分析的负荷,适合于连续数据分析,能够准确地反映脑电维数复杂度的连续变化过程.     

相空间脑电描记法:一种手术期脑电分析的新方法

手术期脑电图的监护有助于对大脑功能完整性和麻醉深度进行评价。本文作者介绍了一种由计算机产生的技术,利用此项技术能产生一幅将脑电图数根绘制成相空间图的增强显示图象并经数学推导得到一个可能与麻醉深度有关的参数(维数)。用以描述复杂的动态系统的非线性数学分析,能通过识别特征模式(相空间中与特定有序的脑电信息相对应的几何形状)和对有序,无序程度的定量(维数计算)来描述相空间脑电图的特性。维数计算描述一种信号复杂程度并能得出一个具有临床意义的表示麻醉深度的单变电脑电图描述符。在文章中,作者描述并论证了由正弦波、正弦合成波及白噪声(随机无序现象)得到的相空间图。作者还显示了一名患者的脑电相空间图和维数计算结果,这是一     

多道脑电信号时间序列的非线性动力学分析

目的：探讨脑电非线性动力学分析中的多道记录方法。方法：通过仿真数据和实际电脑电数据求出其相关维数,并比较基于多道脑电记录和基于单道脑电重构的两种方法。结果：在噪音条件下,多道脑电记录计算得到的相关维数D2曲线具有更好的线性区域,从而可得到更稳定的估计值。结论：从多道脑电时间序列提取的系统特征参数。较单道重构的结果更稳定和可靠,更能反映大脑动力学系统的全貌,值得进一步研究。     

多导信号的相空间重构及在脑电信号分析中的应用

本研究提出了一种基于时间延迟和序列相关性的多导信号相空间重构方法。根据信号的相关系数重组多导联信号序列，并利用信号的可确定性选取时间延迟参数重构相空间。对仿真数据的研究表明这种重构方法在信号的确定性和相关维数计算中具有良好的性能，受噪声、延迟量和嵌入维数等参数变化和单导重构相比影响较小，结果更稳定和可靠。对实验思维脑电数据的非线性分析得到了脑电和思维复杂性，关联性等性质的联系。该方法适用于短时多导含噪信号的非线性分析和脑电的在线研究等。     

电刺足三里穴脑电信号的非线性动力学方法初探

为探讨电刺足三里穴位引起的大脑活动的变化，本文以脑电为手段，用非线性动力学方法对电刺前后的两种脑电的非线性特征进行分析。实验结果显示，非线性特征指数，如关联维数、Lyapunov指数和测度熵，在电刺前后均能很好的区分（P〈0．05）。结果表明，电刺后大脑的随机性和无序度降低，大脑相应脑区的活动更趋于有序，且这种有序性将随着电刺次数的增加而渐趋于稳定。     

局限性癫痫脑电时间序列的分形维数计算比较

为探索应用非线性动力学理论诊断癫痫病的新方法，对局限性癫痫病患者脑电时间序列进行了相关维数（Ｄｃ）和波形维数（Ｄｗ）的计算比较。观察到，痫性导联脑电的分形维数多低于对侧导联的值；相关维数Ｄｃ的相对变化量较波形维数Ｄｗ大；而波形维数Ｄｗ对痫性棘波敏感；结果提示，脑电时间序列的分形维数有可能成为诊断癫痫的特征参数，值得进一步深入研究。     

动态分析急性心肌缺血模型中的非线性

通过分析心脏电信号 ,许多学者已经发现正常的心脏和病态的心脏都有显著而突出的动力学特征。在此基础上 ,建立了 6只兔子急性心肌缺血实验模型 ,计算其不同时间段的 12导同步 ECG,作出关联维数 -时间 (D2- T)曲线和最大 L yapunov- T曲线 ,结合电生理和解剖学知识 ,研究了实验结果 ,证实了心肌缺血的存在会导致ECG的最大 L yapunov指数和关联维数的下降。 ECG的最大 L yapunov指数和关联维数分别反映了心脏系统的混沌性和复杂性 ,两者间没有明确的对应关系。关联维数更多受到了局部心脏系统状态的影响。     

The nonlinear dynamical analysis of the EEG in schizophrenia with temporal and spatial embedding dimension

We applied nonlinear dynamics theory to EEG analysis of schizophrenic patients and estimated the correlation dimension with both temporal embedding and spatial embedding. A higher D₂ was found when using a time-delay embedding method. Especially at F₇ and Fp₁, a significant increase showed. We concluded that more complex activity occurred in certain lobes of schizophrenic patients. Using the spatial embedding method, a relative lower global correlation dimension was obtained. This shows that there might be a diffuse slow wave activity through a schizophrene's global cerebrum. Finally, we discuss the study from three angles of clinical semiology, spectrum analysis and neuropsychology and draw some conclusions about the relationship between the nonlinear analysis of schizophrenia EEG and clinical research. It seems that the theory of a nonlinear dynamics system is a powerful tool for EEG research and may prove useful in complementing visual analysis of EEG accompanied with other study means for brain electrical activity.     

睡眠脑电的关联维数和近似熵分析

睡眠的正确分期是睡眠研究的基础,脑电的非线性参数可以表征不同的睡眠状态。本研究计算睡眠脑电的关联维数和近似熵,通过统计和比较发现关联维数不随嵌入维数的增加而饱和,但其相对大小能有效区分各种睡眠状态;近似熵计算简单,性能稳定,可较好地表征不同睡眠期;相对关联维数和近似熵从不同角度表现了脑电(大脑)复杂性的相同演变规律清醒时复杂性最高,而且波动最大,随着睡眠加深,复杂性降低且变异减小,REM期复杂性基本介于S1期和S2期之间。     

Correlation dimension analysis of the artificial circulation

Artificial circulation has been analyzed by decomposing it into parts. However, the sum of the decomposed parts is not equal to the whole system, especially in nonlinear dynamic systems such as biological systems. To evaluate prosthetic circulation as an entity, not as decomposed parts, nonlinear mathematical analytic techniques, including fractal dimension analyzing theory, were used. Two pneumatically actuated ventricular assist devices were implanted as biventricular bypasses (BVB) in chronic animal experiments using four healthy adult goats. For comparison between natural and prosthetic circulation in the same experimental animals, the BVB-type complete prosthetic circulation model with ventricular fibrillation was adopted. All hemodynamic parameters with natural and prosthetic circulation were recorded under awake conditions and calculated by a personal computer system. By the use of nonlinear mathematical techniques, time-series data of the hemodynamics were embedded into the phase space, and correlation dimension analysis was performed to evaluate the reconstructed attractor. Our results suggest that the correlation dimension of the arterial blood pressure does not linearly increase according to the increase of the embedding dimension, even during artificial circulation, suggesting those are the fractal time series data. Dimensional analysis of the hemodynamics revealed that lower dimensional fractal dynamics were observed during prosthetic circulation. Fractal time series data are suggested to have robustness and error resistance. Thus, our results suggest that the circulatory regulatory system with the artificial heart may have these desirable characteristics. Accepted: July 14, 1995     

HAI实验中EEG信号的非线性动力学研究

采用一维时间序列相空间重构技术和混沌的定量判据，对缺氧窒息而引起的中枢神经损伤（Hypoxic-Asphyxic Injury，HAl）实验中仔猪的脑电（Electroencephalogram，EEG）信号进行了分析与计算。通过对生理和损伤状态下仔猪EEG信号的相图、功率谱、关联维数和Lyapunov指数的对比研究，得出如下结论：（1）EEG的相图、功率谱、关联维数和Lyapunov指数反映了大脑的总体动态特征，它们可作为一种定量研究EEG的新方法进行脑损伤的早期诊断；（2）在正常的生理状态下EEG是混沌的，而在损伤状态下则趋于有序。     

On the discrimination of patho-physiological states in epilepsy by means of dynamical measures

In the present paper a number of techniques were applied to determine the effects of epileptic seizure on spontaneous ongoing EEG. The idea is that seizure represents transitions of an epileptic brain from its normal (chaotic) state to an abnormal (more ordered) state. Some nonlinear measures including correlation dimension, maximum Lyapunov exponent and wavelet entropy and a graphical tool, named recurrence plot, as well as a novel technique that collects some statistics of the state space organization were used to characterize interictal, preictal and ictal states and derivate a phase transition. The novelty of this work includes of introducing new types of indicators base upon some nonlinear features besides of proposing a new feature of point distribution in phase space. Our results show that (1) these three states are separable in 3-D feature space of nonlinear measures with a gradual decrease of their quantity in seizure evolution, (2) strong rhythmicity, which manifests in recurrence plots and recurrence quantification analysis measures, appears in dynamic while having entered into seizure and (3) different volumes of state space are occupied during each phase of epileptic disorder.The significance of the work is that this information is a step into the detection of a preictal state and consequently is helpful in the prediction and control of epileptic seizures.     

Investigation of brain potentials in sleeping humans exposed to the electromagnetic field of mobile phones

An investigation was made of 8-hour EEG tracings of sleeping humans exposed to the electromagnetic field of a GSM-standard mobile phone. To analyze the EEG-patterns, manual scoring, nonlinear dynamics, and spectral analysis were employed. It was found that, when human beings were exposed to the electromagnetic field of a cellular phone, their cerebral cortex biopotentials revealed an increase in the alpha-range power density as compared to the placebo experiment. It was also found that the dimension of EEG correlation dynamics and the relation of sleep stages changed under the influence of the electromagnetic field of a mobile phone.     

Comparisons of the nonlinear dynamics of electroencephalograms under various task loading conditions: a preliminary report

Comparison of the characteristics of electroencephalogram (EEG) records treated as realizations from a nonlinear process were compared under four different conditions: eyes shut resting, and three silent observation instructions to predict the patterns of randomly generated lights which illuminated every 10 seconds. The correlation dimension of the EEG was calculated by a method involving finding the correlation integral in m-dimensional space, and found to show some variations within time series. The degree and directions of changes in the dimensionality of the process varied between observers and did not clearly confirm some earlier reported findings, but it is demonstrable that the measures of nonlinear brain dynamics can be correlated with psychological variables. Reasons for this are discussed.