一新型的脑电有线传输技术

本文介绍了一种新的脑电信号有线传输技术：经公共电话网络、通过一个调频信道、利用时分多路复用方式可同步传输多达20导联的脑电信号;通过另一个调频信道,接收方还能实时获知受测试者的当前意识状态以及实现收发双方的同步。经在此基础上开发的脑电遥测系统的使用验证：该技术能涵盖大部分临床诊断的实际需要、并且信号的传输质量较好、失真度小、无明显噪声污染、无基漂。     

脑电遥测技术的研究

本文提出了一种新型的脑电遥测技术。利用两个调频信道、通过公用电话线进行信号传输：其中一个调频信道采用时分多路复用的方法实时传输多导联脑电信号;另一个调频信道则同步发遂状态参数以供接收方进行数据标识或同步处理。该技术能涵盖任何常规临床诊断的实际需要,并且波形传输质量好、失真度小、无明显噪声污染、无基漂,具有较高的应用价值。     

多导联脑电遥测与远程监护系统的研制

介绍了一种脑电实时遥测与监护系统的研制，通过公共电话线网络进行信号传输，利用便携式脑电记录系统作为系统的发射端，可同步传输20导联的脑电信号到系统接收端（监控中心），同时监控中心可对波形进行实时滚动显示，冻结，存储，回放，分析以及打印，为远程诊断提供依据和治疗指导。     

基于功率谱峰值及时变线性分类算法的运动意识分类

背景:脑电信号的特征提取是脑机接口系统中一个重要的环节,如何快速有效地提取反映大脑意识任务状态的脑电特征是进行分类、正确解读意识任务的关键。目前,提取脑电信号特征通常采用功率谱密度估计、自回归模型和小波变换等方法,这些特征都是以脑电信号的线性化为前提,上述方法不能很好地反映出大脑的非线性动力学性质。目的:分析脑电信号功率谱峰值在识别左右手想象运动中的作用。方法:采用脑机接口2003竞赛中Graz科技大学提供的脑电数据,用小波包分解获取8～24Hz脑电信号,计算C3,C4电极脑电信号的功率谱峰值作为脑电特征向量,运用时变线性分类算法对运动意识任务运行分类。结果与结论:对140次实验的测试样本进行数据分析,最大分类正确率可达89.29%,最大互信息和信噪比分别为0.6269bit和1.3848。C3,C4电极8～24Hz脑电信号功率谱峰值能很好地反映左右手运动想象脑电特征的变化,与事件相关去同步/事件相关同步现象变化一致,可在线识别左右手想象运动。     

基于脑电alpha波及运动想象的在线脑机接口系统设计

背景：目前在线脑机接口系统绝大多数采用同步式设计,无法区分“工作”状态与“空闲”状态。 目的：设计一种能够自由在“工作”与“空闲”状态间切换,方便灵活的脑机接口系统。 方法：设计了综合睁眼产生的alpha波阻断现象,以及进行运动想象时产生事件相关同步及去同步现象这些生理特征的在线脑机接口系统。通过检测使用者枕部脑电信号alpha波状况,来切换“空闲”与“工作”状态;在“工作”状态下,通过想象不同的肢体运动,分析运动皮质脑电信号的频率特征,来实现对外界的信息传输。 结果与结论：实验证明,经过训练的使用者在该在线脑机接口平台上可以自如的在不同状态间进行切换,并且能以很高的分类正确率发出控制命令。采用此方法进行设计,脑机接口系统的实用性得到了增强。     

不同麻醉深度下大鼠脑电复杂度和功率谱的变化过程

本研究计算和分析了大鼠在逐渐加深的Urethane麻醉过程中脑电信号的算法复杂度、近似熵、功率值和功率谱重心频率的变化特征。结果表明：随着麻醉程度的加深，皮层脑电中同步波的两种复杂度值逐渐减小，同步波高频段功率也逐渐减少，使得功率谱重心频率向低频方向迁移；去同步波则在深度麻醉状态下不再出现，说明中脑网状结构的激励已消失。另外，脑电信号的算法复杂度和近似熵的计算结果有很好的一致性。     

脑肌电信号同步耦合分析方法研究进展

运动神经系统通过神经振荡活动传递运动控制信息,从而引起相应肌肉的同步性振荡活动并反映运动响应信息,然后反馈至大脑皮层,使其能够感知肢体的状态。这种同步振荡活动可反映皮层肌肉功能耦合的连接信息。其中,耦合的强弱由多种因素决定,包括肌肉收缩的力量、注意力、运动意图等,因此分析不同因素影响下的脑肌电信号同步耦合的强弱对运动功能评价及控制方法等研究有重要意义。针对脑肌电信号同步耦合的分析方法,本文主要介绍与比较了线性方法中的相干性分析和格兰杰因果分析,以及非线性方法中的互信息以及传递熵,总结了各方法在脑肌电信号同步耦合的应用研究,以便于相关领域的科研工作者更系统地了解目前脑肌电信号同步耦合分析方法的研究进展。     

不同导同步脑电波信号的DFA分析

通过对欧洲格式(EDF)的两个同步导脑电波信号Fpz—Cz及PZ—Oz DFA的分析，表明这两个导的DFA结果有显著差异，PZ—Oz的分析结果和MIT脑电信号的分析结果类似；而Fpz—Cz的分析结果则明显不同。表明不同导的脑电信号可能具有完全不同的长程相关性质。因此，利用DFA方法判读睡眠阶段时，要选择合适的导。     

家庭远程医疗监护数据的传输及处理

介绍了家庭远程医疗监护系统，利用VB编程通过Intemet实现了监护数据的远程传输，医疗中心对接收到的监护数据可以进行去噪、去干扰、特征提取等预处理。在此基础上，实现脑电信号的远程传输，并对医疗中心接收到的脑电信号进行独立成分分析(ICA)分离眼动干扰的处理，取得了较好的效果。     

EEG柯尔莫哥洛夫熵测度用于精神疲劳状态的研究

为了区分精神疲劳的程度，研究了不同精神疲劳状态时脑电信号的无序程度。通过对8例不同精神疲劳状态与其对应脑电信号柯尔莫哥洛夫熵的分析，发现：1）脑电信号柯尔莫哥洛夫熵的波动范围与精神疲劳的状态有着明显的对应关系；2）脑电信号柯尔莫哥洛夫熵随着连续工作时间的延长而减小；3）可以通过分析脑电信号柯尔莫哥洛夫熵的波动范围对疲劳时心理生理状态进行客观评定。研究方法为进一步认识精神疲劳的过程、研究精神疲劳对中枢神经系统的影响提供了一种新的工具。     

A multichannel telemetry system for recording cardiovascular neural signals.

A multichannel telemetry system was developed for use with chronically instrumented unrestrained cats. This system can simultaneously record efferent and afferent cardiovascular neural signals, bioelectrical noise arising near the electrode recording the neural signals, EEG, ECG, and a standard calibration signal. The miniature (18 cm3), lightweight (24 g), telemeter is a five-channel, time-multiplexed, pulse width modulation (PWM)/FM device employing a high frequency subcarrier (60 kHz) and two sampling frequencies (30 kHz and 6 kHz). The device is powered by two small 120 mA . h silver oxide cells; it has an indoor transmission range of 10 m and can operate for 48 h. One channel transmits a standard signal (a square wave of 100 Hz and 200 mVp-p) used to monitor and regulate the system's performance. When the variation in either the amplitude or frequency of the standard signal is greater than 10% of the control value, the transmitted bioelectrical signals are automatically discarded.     

睡眠EEG的多尺度信息熵分析

本文提出一种基于连续小波变换的睡眠EEG分析方法。该方法使用Morlet小波计算EEG信息的小波变换系数,通过计算EEG信号在多个尺度上小波系数的熵分析睡眠EEG。结果表明：浅睡阶段EEG信号的多尺度熵的变化模式与深睡阶段的多尺度熵的变化模式不同,REM睡眠期间EEG信号的多尺度熵的变化与深睡阶段类似,使用多尺度熵可以区分REM睡眠和浅睡时EEG之间的差别。     

A chaos-based model for low complexity predictive coding scheme for compression and transmission of electroencephalogram data

A method for low complexity, low bit rate transmission of EEG (electroencephalogram) data, based on chaotic principles, is presented. The EEG data is assumed to be generated by a non-linear dynamical system of E dimensions. The E dynamical variables are reconstructed from the one-dimensional time series by the process of time-delay embedding. A model of the form X[n + 1] = F(X[n], X[n - 1], ... , X[n - p]) is fitted for the data in the E-dimensional space and this model is used as predictor in the predictive coding scheme for transmission. This model is able to give a reduction of nearly 50% of the dynamic range of the error signal to be transmitted, with a reduced complexity, when compared to the conventionally used linear prediction method. This implies that a reduced bit rate of transmission with a reduced complexity can be obtained. The effects of variation of model parameters on the complexity and bit rate are discussed.     

A chaos-based model for low complexity predictive coding scheme for compression and transmission of electroencephalogram data

A method for low complexity, low bit rate transmission of EEG (electroencephalogram) data, based on chaotic principles, is presented. The EEG data is assumed to be generated by a non-linear dynamical system of E dimensions. The E dynamical variables are reconstructed from the one-dimensional time series by the process of time-delay embedding. A model of the form X[n+1]=F(X[n], X[n−1],...X[n−p]) is fitted for the data in the E-dimensional space and this model is used as predictor in the predictive coding scheme for transmission. This model is able to give a reduction of nearly 50% of the dynamic range of the error signal to be transmitted, with a reduced complexity, when compared to the conventionally used linear prediction method. This implies that a reduced bit rate of transmission with a reduced complexity can be obtained. The effects of variation of model parameters on the complexity and bit rate are discussed.     

Interdependence of EEG signals: Linear vs. nonlinear Associations and the significance of time delays and phase shifts

Summary To investigate the degree of interdependence of EEG signals, we have to use signal analysis methods. Three of these are described and their performance is compared: the cross-correlation (coherence and phase), the average amount of mutual information (AAMI) or the normalized AAMI, also called transmission coefficient T, and the correlation ratio h² that is a general measure of nonlinear fit between any two signals. The three methods were applied to simulated and real signals in order to put in evidence how nonlinear relationships may affect differently these three measures of association. The nature of the interdependence between EEG signals is not characterized only by the degree of association, but also by the corresponding phase relationship. A basic question is whether such a phase shift can be interpreted as a transmission delay. However, a fundamental problem is that a phase shift may be difficult to interpret in terms of a biophysical model. A procedure is described in order to solve this problem. This involves computing the phase spectrum between the pair of signals, estimating the gain of the corresponding linear transfer function and the associated minimum phase. By subtracting the minimum phase from the phase spectrum, a corrected phase function can be obtained. From the slope of this phase function, a transmission delay can be estimated. This procedure is illustrated by applications to simulated and real EEG signals. It is demonstrated that from phase shifts we may estimate transmission delays between at least certain classes of EEG signals. In this way we can asses, unambiguously, how the transmission of information between different brain sites develops.     

A miniaturized four-channel radio transmitter with receiving system for obtaining physiological data from birds

A miniaturized FM/FM four-channel radio transmitter was developed for telemetering physiological data. The transmitter weighs 24 g and has a volume of 1·5 cu. in. Transmitting frequency is 91 Mc/s and stable signal reception has been obtained at a distance of 200 ft. The system was developed to simultaneously study EEG, ECG, respiration, and temperature of wild birds such as pigeons (Columba livia), but its application is not limited to birds. With proper selection and placement of sensors and transducers, physiological parameters other than the above may be measured. The transmitter meets IRIG (Inter Range Instrumentation Group) standards for channels 13, 14, 15, and 16, and a receiving system that meets these standards can be used to filter and demodulate the transmitted signal.     

基于Java3D的虚拟飞机脑机交互应用系统设计

目的本文基于Java3D设计了虚拟飞机脑机交互（braincomputerinterface,BCI）应用系统．研究BCI对虚拟飞机的控制效果。方法通过TCP／IP协议将BCI中对脑电信号（electroencephalogram．EEG）分析处理的结果传给Java3D应用系统,进而将结果转换成对应的控制命令,实现实时控制虚拟飞机的飞行,可以直观反映并检验BCI的控制效果。应用系统的设计分为两个步骤：一是搭建三维虚拟场景,其中包括建立场景模型和设计场景的布局;二是虚拟飞机飞行控制的设计,以实现飞机前进和旋转的飞行控制。结果本应用系统能够实时正确通过TCP／IP接收EEG信号的分析结果,实时控制虚拟飞机的连续飞行运动。结论初步验证了Java3D应用系统的可行性,为BCI应用系统的设计提供了新的方法和发展方向。