基于复杂性测度的EG初步研究

利用两种复杂性测度的方法对正常人和病人不同大脑负荷状态下的EEG进行了分析。一种是Kaspar和Schuster定义的复杂度算法，一种是新的度量序列复杂度的统计方法－近似熵。通过对若干例在四种不同 实验状态下的EEG信号的分析，表明可通过两种算法的数值变化有效地分辨大脑的状态：正常或病理以及不同的负荷状态。而且两种复杂性测度算法的变化规律相同。显示出两种复杂性测度的算法在EEG序列的研究和临床诊断中有广阔的应用前景。     

精神分裂症脑电在不同认知作业下的复杂度分析

为探讨在不同认知作业状态下精神分裂症患者脑电复杂性测度的变化规律,本文利用Lempel-Ziv复杂性测度方法对62例精神分裂症患者和26例正常人群在三种不同精神状态安静闭目、闭眼心算连减和数字划消下的16导联脑电数据进行了分析.实验结果得出:精神分裂症患者和正常在三种精神状态下某些导联复杂性测度的大小有明显差异,复杂度的空间分布规律相似;与安静闭目状态下相比,完成认知作业的两种状态下EEG的复杂度都偏低(a=0.01).认为复杂性测度分析适合研究认知过程中大脑功能活动的变化规律,有助于了解认知过程中大脑的工作机制.     

早老性痴呆的脑电复杂度与近似熵特征分析

利用两种复杂性测度的算法(复杂度与近似熵)对早老性痴呆(AD)病人和正常人的脑电进行分析,并绘制脑电信息图(BIM).通过对比表明AD患者头皮绝大多数导联处EEG信号的复杂性测度值均显著低于同龄正常人,平均有20%～40%的降幅,而且信息图灰度值都小于正常人.研究结果提示EEG的复杂性测度与大脑功能状况有一定联系,在一定程度上可以反映大脑功能状态的变化.     

EEG复杂性测度用于大脑负荷状态的研究

Ｌｅｍｐｌ－Ｚｉｖ意义下的随机序列的复杂性反映了有限长序列的随机程度。本文研究了大脑不同负荷状态时脑电图的复杂性，分析了大脑负荷状态与相应状态下ＥＥＧ复杂度之间的关系。     

生理信号时问序列周期性和平稳性对近似熵和样本熵算法的影响分析

目的提高近似熵和样本熵算法在评价生理信号时间序列非线性复杂度应用中的精度。方法首先生成生理信号时间序列数据库,通过对周期序列和叠加有周期成分的非线性序列的分析,研究序列周期性对熵测度算法的影响,并通过对心率变异性（hear trat evariability,HRV）序列在去除非平稳趋势前后的对比分析,研究序列平稳性对熵测度算法的影响。结果在序列长度范围内,不同重复频率的周期序列熵测度不同,不同比重的周期成分叠加到非线性序列中引起序列熵测度的变化也不同。生理信号时间序列中大都存在非平稳成分,而非平稳成分会降低序列的复杂度,因此进行熵测度计算前首先要去除非平稳成分。结论周期性和非平稳成分显著影响生理信号时间序列的熵测度算法。     

基于独立分量分析算法研究儿童癫痫脑电的混沌动力学特征

首先采用独立分量分析(Independent component analysis,ICA)算法,将儿童癫痫信号从复杂的背景脑电(Electroencephalogram,EEG)中分离出来;然后采用了一维时间序列相空间重构技术和混沌的定量判据,对分离出来的独立分量信号进行了分析与计算.通过对生理和癫痫状态下独立分量信号的相图、功率谱、关联维数和Lyapunov指数的对比研究,得出如下结论:(1)EEG独立分量的相图、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指标衡量大脑的健康状态;(2)在正常的生理状态下EEG是混沌的,而在癫痫状态下则趋于有序。     

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.     

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。     

不同睡眠期脑电图复杂性研究

ＥＥＧ代表了大脑神经元活动的一种电信号，它一直是研究人在不同睡眠阶段大脑活动的重要工具。本文在国际睡眠分期标准的基础上，利用Ｌｅｍｐｅｌ－Ｚｉｖ所定义的随机序列的“复杂性”对不同睡眠期的ＥＥＧ时间序列了分析和研究。结果显示，随被试睡眠深度的增加，各道ＥＥＧ的复杂度减少。而在ＲＥＭ期，ＥＥＧ的复杂度又回升到接近清醒、闭眼休息时的程度。这个规律不受是位置的影响。对结果的分析可以看到，复杂度能成为反映民     

多尺度交叉熵及其在血压与肾交感神经活动耦合模式中的应用

多尺度熵反映了单个时间序列在多个尺度上的复杂性,本研究提出了多尺度交叉熵的概念和算法,并探索两个时间序列在多个尺度上的耦合行为.首先,将其应用到一个混沌动力学系统的分析中,即Henon-Henon映射.然后,应用多尺度交叉熵分析清醒和麻醉两种状态下血压与肾交感神经活动的非线性耦合模式.结果表明,肾神经活动和血压之间耦合可能具有分形动力学的特征,其复杂度在麻醉后显著降低,而且两种状态下的耦合模式具有明显的差异.     

基于复杂性测度的帕金森症病人EEG分析

ＥＥＧ代表了大脑神经元活动的一种电信号,它一直是人们分析和研究大脑活动和大脑功能状态的重要工具,我们利用了由Ｋｏｌｍｏｇｏｒｏｖ和徐京华定义的ＫＣ复杂性和Ｃ１复杂性,对帕金森症患者和正常人的ＥＥＧ时间序列作了分析和研究,根据４００例的统计结果表明,复杂性能够区分这两者,我们认为这种方法可能作为诊断帕金森症的客观指标。     

Comparative Analysis of EEG Signals Based on Complexity Measure

The aim of this study is to identify the functions and states of the brains according to the values of the complexity measure of the EEG signals. The EEG signals of 30 normal samples and 30 patient samples are collected. Based on the preprocessing for the raw data, a computational program for complexity measure is compiled and the complexity measures of all samples are calculated. The mean value and standard error of complexity measure of control group is as 0.33 and 0.10, and the normal group is as 0.53 and 0.08. When the confidence degree is 0.05, the confidence interval of the normal population mean of complexity measures for the control group is （0.2871,0.3652）, and （0.4944,0.5552） for the normal group. The statistic results show that the normal samples and patient samples can be clearly distinguished by the value of measures. In clinical medicine, the results can be used to be a reference to evaluate the function or state, to diagnose disease, to monitor the rehabilitation progress of the brain.     

Application of fractal theory in analysis of human electroencephalographic signals

In medical discipline, complexity measure is focused on the analysis of nonlinear patterns in processing waveform signals. The complexity measure of such waveform signals is well performed by fractal dimension technique, which is an index for measuring the complexity of an object. Its applications are found in diverse fields like medical, image and signal processing. Several algorithms have been suggested to compute the fractal dimension of waveforms. We have evaluated the performance of the two famous algorithms namely Higuchi and Katz. They contain some problems of determining the initial and final length of scaling factors and their performance with electroencephalogram (EEG) signals did not give better results. In this paper, fractal dimension is proposed as an effective tool for analyzing and measuring the complexity of nonlinear human EEG signals. We have developed an algorithm based on size measure relationship (SMR) method. The SMR algorithm can be used to detect the brain disorders and it locates the affected brain portions by analyzing the behavior of signals. The efficiency of the algorithm to locate the critical brain sites (recurrent seizure portion) is compared to other fractal dimension algorithms. The K-means clustering algorithm is used for grouping of electrode positions.     

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。     

简化EEG为符号序列及对其复杂度的研究

本文将ＥＥＧ简化为符号序列并用复杂度算法对其进行分析。为获得更好结果，对ＥＥＧ的简化方法作了一些改进，提出计算脑电信号的高阶复杂度；为利用脑电信号中的空间信息，又提出计算脑电信号的空间相关复杂度。计算了多例正常人和癫痫病人的各阶复杂度及空间相关复杂度，获得了较好的结果。     

Analysis of EEG background activity in Alzheimer's disease patients with Lempel-Ziv complexity and central tendency measure

In this study we have investigated the electroencephalogram (EEG) background activity in patients with Alzheimer's disease (AD) using non-linear analysis methods. We calculated the Lempel-Ziv (LZ) complexity - applying two different sequence conversion methods - and the central tendency measure (CTM) of the EEG in 11 AD patients and 11 age-matched control subjects. CTM quantifies the degree of variability, while LZ complexity reflects the arising rate of new patterns along with the EEG time series. We did not find significant differences between AD patients and control subjects' EEGs with CTM. On the other hand, AD patients had significantly lower LZ complexity values (p<0.01) at electrodes P3 and O1 with a two-symbol sequence conversion, and P3, P4, O1 and T5 using three symbols. Our results show a decreased complexity of EEG patterns in AD patients. In addition, we obtained 90.9% sensitivity and 72.7% specificity at O1, and 72.7% sensitivity and 90.9% specificity at P3 and P4. These findings suggest that LZ complexity may contribute to increase the insight into brain dysfunction in AD in ways which are not possible with more classical and conventional statistical methods.     

Single-dose piracetam effects on global complexity measures of human spontaneous multichannel EEG.

Global complexity of 47-channel resting electroencephalogram (EEG) of healthy young volunteers was studied after intake of a single dose of a nootropic drug (piracetam, Nootropil UCB Pharma) in 12 healthy volunteers. Four treatment levels were used: 2.4, 4.8, 9.6 g piracetam and placebo. Brain electric activity was assessed through Global Dimensional Complexity and Global Omega-Complexity as quantitative measures of the complexity of the trajectory of multichannel EEG in state space. After oral ingestion (1-1.5 h), both measures showed significant decreases from placebo to 2.4 g piracetam. In addition, Global Dimensional Complexity showed a significant return to placebo values at 9.6 g piracetam. The results indicate that a single dose of piracetam dose-dependently affects the spontaneous EEG in normal volunteers, showing effects at the lowest treatment level. The decreased EEG complexity is interpreted as increased cooperativity of brain functional processes.