局灶性癫癎发作间期和发作期的脑电图在致癎灶定侧中的意义

目的:探讨局灶性癫癎发作间期和发作期脑电图变化特点及其在致癎灶定侧中的作用。方法:分析100例局灶性癫癎患者的发作间期、发作期脑电图及发作症状所提供的致癎灶侧别信息。结果:在这100例局灶性癫癎发作患者中,发作间期、发作期脑电图和发作症状可提供明确的致癎灶定侧的信息者分别为53例、76例和73例。结论:在致癎灶定侧诊断中,发作期与发作间期脑电图相比,可提供较高比例的侧别信息;综合分析发作间期、发作期脑电图和发作症状,可以使大部分局灶性癫癎发作的患者获得致癎灶的定侧信息,并为进一步埋置颅内电极,精确定位癫癎灶提供重要的参考。     

A Novel Approach Based on Data Redundancy for Feature Extraction of EEG Signals

Feature extraction and classification for electroencephalogram (EEG) in medical applications is a challenging task. The EEG signals produce a huge amount of redundant data or repeating information. This redundancy causes potential hurdles in EEG analysis. Hence, we propose to use this redundant information of EEG as a feature to discriminate and classify different EEG datasets. In this study, we have proposed a JPEG2000 based approach for computing data redundancy from multi-channels EEG signals and have used the redundancy as a feature for classification of EEG signals by applying support vector machine, multi-layer perceptron and k-nearest neighbors classifiers. The approach is validated on three EEG datasets and achieved high accuracy rate (95–99 %) in the classification. Dataset-1 includes the EEG signals recorded during fluid intelligence test, dataset-2 consists of EEG signals recorded during memory recall test, and dataset-3 has epileptic seizure and non-seizure EEG. The findings demonstrate that the approach has the ability to extract robust feature and classify the EEG signals in various applications including clinical as well as normal EEG patterns.     

Signal separation of background EEG and spike by using morphological filter

A signal separation method for extracting background electroencephalogram (EEG) from EEG containing spikes was proposed. Morphological filters were designed for extracting spike waveforms, and then the background EEG was obtained by subtracting the detected spike waveforms from the EEG with spike. The proposed method was evaluated by using simulated EEG data, which consisted of a summation of EEG without spike and model waveform of typical spike. The background EEG separated by the method was processed by the automatic background EEG interpretation.     

脑电正问题的模型和算法

脑电研究对探索脑神经活动规律、研究脑的认知功能具有重要的科学意义和临床应用价值。脑电研究领域的两个关键问题是脑电正问题和脑电逆问题。脑电正问题是脑电逆问题的基础 ,是根据已知头模型内的电流分布求解头表电位 ,正问题算法的精度和效率是求逆方法成败的关键。本文回顾了近年来问题中发展起来的源模型、头模型以及相应的算法 ,并对今后脑电正问题的研究工作做了展望     

长程视频脑电图监测癫痫发作及在致痫灶定位中的意义

目的：探讨癫痫发作间期和发作期脑电图（EEG）变化特点与发作症状在致痫灶定位中的作用。方法：对80例癫痫患者进行视频脑电图（VEEG）监测,分析其发作间期、发作期EEG特点及临床发作表现作致痫灶定位。结果：80例癫痫患者中,发作间期38例和发作期60例EEG及59例临床发作症状可提供明确的致痫灶定位信息。结论：在致痫灶定位中,发作期与发作间期EEG相比,可提供较高比例的定位信息;综合分析发作问期、发作期EEG和临床发作症状,可以获得大部分癫痫患者致痫灶的定位信息,为放置颅内电极作准确致痫灶定位的重要参考。     

75例颞叶癫癎患者动态EEG与过度换气EEG癎样放电规律探讨

目的：了解睡眠EEG与过度换气EEG的痢样放电规律。方法：评估75例颞叶癫痫患者动态EEG与过度换气EEG的痫样放电特点。结果：过度换气EEG痫样放电检出率明显低于浅睡期EEG，差异具有极显著意义（P〈0．01）；但与清醒期和深睡期EEG痫样放电检出率比较差异无显著意义（P〉0．05）。结论：颞叶癫痫患者浅睡期EEG痫样放电率明显高于过度换气EEG，对颞叶癫痫患者进行睡眠EEG检测，有助于提高痫样放电的检出率。     

基于形态学滤波器的棘波提取技术

本研究提出了一种基于形态学滤波器的脑电棘波检测方法。首先，选择三角形为结构元素，采用数学形态学中的级联开闭和闭开运算分别对脑电信号进行处理，去除癫痫样瞬态信号；然后对级联开闭和闭开运算采用平均加权的方法，消除统计偏倚现象，得到背景脑电信号；最后将处理结果和原始脑电信号做差，提取出脑电信号中的棘波。通过仿真信号的对比分析和临床癫痫脑电信号的应用，表明该方法适用于双向棘波的提取，与以往的方法相比，背景脑电的抑制能力更强，提取出的信号特征成分更完整。     

脑电图监测在新生儿缺氧缺血性脑病中的价值

目的 :观察脑电图 (EEG)监测在新生儿缺氧缺血性脑病 (HIE)中的临床价值。方法 :对 5 0例HIE患儿进行EEG监测并评价EEG结果与临床后遗症的关系。结果 :EEG总异常率为 6 2 % (31/ 5 0 ) ,轻、中和重度异常率分别为 2 9%、4 8%和 2 3% ,临床病情轻、中和重度HIE患儿EEG异常率分别为 2 6 %、77%和 10 0 %。EEG轻度异常者其临床后遗症发生率为 4 % ,EEG中、重度异常者其发生率则为 38%。结论 :EEG异常率与HIE临床病情轻重程度呈正相关 ,EEG异常程度越重则临床后遗症发生率越高。     

„Unspezifische“ EEG- Veränderungen – Verlangsamungen fokal und generalisiert,Asymmetrien

Abnormal EEG are divided in “nonspecific” abnormal EEG pattern with low correlation to an underlying pathogenic process, and a more “specific” abnormal EEG pattern with a higher correlation to an underlying pathogenic process, realizing that “specific” abnormal EEG pattern sensu stricto does not exist. “Nonspecific” abnormal EEG pattern is described and illustrated by EEG recordings.     

脑萎缩的脑电图表现及临床分析

目的:探讨脑萎缩的脑电图(EEG)特点。方法:对75例脑萎缩患者EEG进行分析。结果:75例脑萎缩患者EEG轻度异常37例,中度异常15例,重度异常1例。结论:EEG检查对脑萎缩有一定的临床价值。     

脑电图在闭合性轻、中型脑损伤中的应用价值

目的探讨脑电图（EEG）在闭合性轻、中型脑损伤中的诊断和预后价值。方法本组86例闭合性轻、中型脑损伤住院患者,入院3d内进行EEG检查,EEG异常者于15d后复查,根据EEG异常情况继续跟踪检查,并与有关CT资料对比。结果本组86例患者,轻型脑损伤33例中EEG异常8例,异常率24．2％;中型脑损伤s3q4中EEG异常27例,异常率50．9％。经复查,轻型脑损伤异常EEG均恢复正常,中型脑损伤仍有11例EEG异常,随访观察,还有4例呈痫样放电。结论EEG能客观反映脑损伤后脑功能状况,EEG好转与临床症状呈平行关系,EEG还可早期发现继发性病变如外伤性癫痫等。EEG对了解大脑损伤程度、部位、脑功能恢复情况及预后判断有一定意义。     

一种基于改进经验模态分解的癫痫脑电识别新方法

在临床癫痫诊断过程中,为了提高癫痫脑电的识别率,能在癫痫发作前期就预测到癫痫疾病,其特征波的提取至关重要。针对这一问题,提出将平行延拓与镜像延拓相结合来改进EMD算法。首先,使用平行延拓的方法,在原始脑电信号的左、右端点处分别预测出一个极值;然后,使用基于镜像延拓的EMD方法,对信号进行镜像延拓,以避免经验模态分解过程中的端点效应;最后,采用支持向量机进行信号的分类识别。算法验证数据取自德国伯恩大学癫痫研究中心的脑电数据库,其中50例是正常脑电信号、50例是癫痫发作间期的脑电信号。实验研究表明：该方法对总测试脑电信号的识别率达到94%。其中,正常脑电信号和癫痫脑电信号的独立识别率均为94%,比传统EMD算法处理后的脑电识别率提高了5%,可见该方法可以有效地预测癫痫脑电。     

下丘脑错构瘤患者的脑电监测5例报告

目的：探讨下丘脑错构瘤的脑电图特点。方法：对5例下丘脑错构瘤患者的术前头皮脑电图和术中皮层脑电图及瘤体电图进行监测，并分析讨论。结果：5例患者均作头皮脑电图、皮层电图及瘤体电图。头皮脑电图发现3例有棘波，瘤体电图2例有棘波，5例皮层脑电图均记录到棘波。结论：下丘脑错构瘤可使邻近皮层产生棘波灶，瘤体内可记录到棘波放电，脑电监测有助于指导临床治疗。     

EEG data filing system with personal computer and magneto-optical disc

We established a new computerized EEG filing system, in which an EEG machine was connected to an EEG filing unit which consisted of a personal computer with a 32 bit CPU, 18 channel analog -to-digital and digital-to-analog converters, and a magneto-optical disc driver. This system has the following merits. The system was space-saving, the space required to store the EEG data, being only 1/500 of that required for storing EEG record. Though the system had two independent EEG filing units, our original file configuration enabled us to have access to all of the recorded EEG data anytime for more than 10 years. The system enabled us to display EEG data continuously on the high resolution CRT, just as if turning the page of an EEG record paper, and through the quick scanning, enabled us to view the entire EEG pattern. Furthermore, the system enabled us to conduct reliable digital analysis for EEG data by entering the EEG data without artifacts into a data processor after confirmation on the display. In the system, we used data files with the MS-DOS operating system. This enabled us to analyze the data obtained by a personal computer operating on other systems, by transferring the data to a floppy disc operating on our system. Our EEG filing system allows quick access to data as well as mass data storage.     

颞叶癫痼患者长程数字化视频EEG与过度换气EEG痫样放电规律探讨

目的：了解长程数字化视频EEG与过度换气EEG的癎样放电规律.方法：评估52例颞叶癫癎患者长程数字化视频EEG与过度换气EEG的癎样放电特点.结果：过度换气EEG癎样放电检出率明显低于浅睡期EEG,差异具有极显著意义（P＜0.01）;但与清醒期和深睡期EEG癎样放电检出率比较差异无显著意义（P＞0.05）.结论：颞叶癫癎患者浅睡期EEG癎样放电率明显高于过度换气EEG,对颞叶癫癎患者进行睡眠EEG检测,有助于提高癎样放电的检出率.     

儿童腹型癫痫的脑电图分析

目的:探讨脑电图对腹型癫痫的诊断价值和疗效观察。方法:使用日本1A97型脑电图仪对131例腹型癫痫的儿童进行检查。结果:脑电图异常127例,总异常率97％。结论:脑电图对腹型癫痫的诊断和疗效观察有重要价值。     

子痫前期脑电图分析

目的研究子痫前期的脑电图表现。方法对124例子痫前期患者进行脑电图检查。结果 53.2%的子痫前期患者脑电图为正常脑电图,除中度异常脑电图结果小组外,轻度子痫和重度子痫患者EEG无统计学差异。结论脑电图评价子痫前期患者敏感性较低。     

脑电在线分析系统的研究及小波变换的应用

在对小波变换及时频特性研究的基础上,对脑电信号进行时频分析,给出EEG小波变换的结果,实现EEG在不同频率尺度的分解和重构,针对脑电信号的特点和分析方法,设计了脑电在线分析系统,阐述了系统软硬件结构设计和实现方法,该系统具有良好的实时性,功能齐全,可用于脑电的分析,监护和反馈研究。     

Technical quality evaluation of EEG recording based on electroencephalographers' knowledge

The aim of this study is to develop a technical quality evaluation system of electroencephalogram (EEG) recording in order to acquire technically satisfactory EEG records, which may contribute to the accuracy improvement of EEG interpretation. In our developed system, the evaluation of EEG recording comprises the detection of technical artifacts and physiological status, which indicates the recording status objectively. In addition, the caution signals to users are generated in the system according to the undesired status detected. The information displayed to users includes the updated EEG records and instant evaluation results. Two examples of evaluation results are introduced in this paper, illustrating unsatisfactory records and artifact free records, respectively. The experimental results are proposed to verify the effectiveness of the technical quality evaluation of EEG recording. The implementation of the technical quality evaluation of EEG recording is helpful to acquire technically satisfactory EEG records, which may improve the accuracy of results in both the visual and the automatic EEG interpretation, and ease the laborious work of EEG technicians in the recording progress.     

Signal processing and quality of displaying waveform at digital EEG machine

With great advances in computer technology, the digital EEG machine was developed and has become widely used. In this paper, signal processing and quality of display of waveform at digital EEG machine were discussed to confirm its advantages and drawbacks. Signal processing on a digital EEG machine is summarized in 3 parts as follows: i) A/D conversion(sampling) of EEG signals in the head box, ii) Digital signal processing to obtain mathematically reconstructed EEG on the computer, iii) Displaying EEG on a monitor. For sampling, it was recommended that sampling rate was 200 or 256 Hz, and resolution in 12 bits or preferably 16 bits per sample. A high amplitude artifact caused EEG flattening called DC build up saturation. Montage reformatting had a clinical advantage. However, re-filtering using 15 Hz high cut filter influenced the EEG interpretation. The maximal resolution of digital EEG machine with a 17-inch CRT display using 1600 x 1200 dots was about 22 Hz. The performance of paper used for conventional EEG surpassed the performance of CRT display using digital EEG machine. It seemed that understanding the characteristics of digital EEG machine and realization of data processing were important for utilizing its functions effectively.