腹型癫痫的临床与脑电图(附35例分析)

本文报道腹型癫痫35例,男18例,女17例。发病年龄4～40岁,平均12.8岁,80％为4～15岁。均表现阵发性腹痛伴植物神经症状,抗癫痫治疗有效。脑电图异常33例(94.3％),正常2例(5.7％)。着重讨论了本病的脑电图表现。认为脑电图检查对本病的诊断及动态观察有重要辅助作用。对难解释的阵发性腹痛行鉴别诊断时应考虑腹型癫痫的可能。     

Spectral entropy analysis of different alpha band rhythms in relation to hand motor imagery

The event-related desynchronization/synchronization(ERD/ERS) time courses of lower and upper alpha band rhythms during hand motor imagery are investigated respectively by Fourier Sectral Entropy (FSE) in this paper. By analyzing one group of BCI competition data, it was found that FSE within upper alpha band displays a pronounced increase and decrease over contralateral and ipsilaterai brain areas respectively at the onset of hand motor imagery, which is corresponding to the antagonistic ERD/ERS patterns in previous studies. Different from the upper alpha activity pattern, FSE within lower alpha band displays a consistent increase over both two hemispheres hand representative areas. The preliminary results show that FSE could disclose the different behaviors of the upper and lower alpha band rhythms so that a new idea with the complexity measure is provided to characterize functional dissociation of lower and upper frequency alpha rhythms in relation to hand motor imagery.     

56例小脑电图研究

采用排除肌电干扰的绝缘针电极记录了56例经头皮的小脑电图。其中41例非器质性脑病患者为对照组，小脑电图是频率与大脑半球一致的低幅α波为主的电活动；8例大脑器质性病变患者的小脑电图与对照组的相似;7例小脑病突患者的小脑电图α波减少、θ波出现。认为用此法测得小脑电图可能成为检测小脑功能状态的一个简便、客观指标。     

隐性缺铁婴幼儿脑功率谱及脑地形图变化研究

采用严格配对的研究方法，对２０对６～３０个月隐性缺铁（ＬａｔｅｎｔＩｒｏｎＤｅｆｉｃｉｅｎｃｙ，ＬＩＤ）婴幼儿进行了脑功率谱和脑地形图分析。结果显示ＬＩＤ患儿在右后顶部、左中后颈、右中颞及前中央顶部α１能量减低，提示ＬＩＤ患儿大脑发育比正常组婴幼儿落后。     

Hilbert-Huang变换结合近似熵在疲劳驾驶时脑电分析中的应用

研究疲劳驾驶状态下驾驶员脑电信号的特征。结合Hilbert-Huang Transform(HHT)方法和近似熵方法,提出了一种新的脑电信号处理方法:HHT近似熵方法,首先用HHT方法把脑电信号分解为多个内在的模式分量,然后求取各个模式分量的近似熵值,探讨疲劳驾驶时脑电信号的非线性特征。在汽车模拟驾驶仪上进行疲劳驾驶,同时用脑电测量仪器测量驾驶员脑电,用HHT近似熵方法对正常静坐、正常驾驶、疲劳静坐、疲劳驾驶4种脑电信号进行具体的分析处理,结果表明d_2、d_4近似熵比值可以区分4种脑电信号,可以作为疲劳驾驶时的脑电特征。为疲劳驾驶的预警系统研究提供了理论上的一些依据和参考。     

驾驶分心检测方法综述

道路交通事故已经成为世界人民非自然死亡的主要原因,有学者认为90%的交通事故与驾驶员自身因素关联,而其中又有超过50%与驾驶分心相关。为了对驾驶员分心进行识别以及为下一步的分心预警干预提供结果判断,文章介绍了常见的驾驶分心检测与识别方法,包括人脸识别方法,眼睛瞳孔位置识别以及基于驾驶员生理信号(EEG)的分心监测方法。结果表明检测方法各有优劣,非接触式、无侵入性检测,对驾驶员行车体验影响小,但测试精度具有一定的局限性。利用头戴仪等接触式设备,对驾驶员具有一定的侵入性,但是与其他检测方式相比,则具有较高的准确性优势。     

二氧化碳人工气腹在安氟醚吸入麻醉中对心率变异性及脑电指标的影响

目的　探讨CO2 人工气腹在安氟醚吸入麻醉中对腹腔镜胆囊切除手术患者心率变异性 (heartratevariability ,HRV)及脑电 (electroencephalogram ,EEG)指标的不同影响。 方法　利用心率变异功率谱分析技术 (HRV PSA)和脑电功率谱分析技术 (EEG PSA)对 2 8例腹腔镜胆囊切除手术患者在麻醉前、麻醉诱导插管后及CO2 人工气腹后HRV指标LF、HF、LF HF、TP及EEG参数BIS、95 %SEF的变化进行了观察。结果　麻醉诱导插管后LF、HF、TP、BIS及95 %SEF均显著降低 ,LF HF未见明显改变 ;CO2 人工气腹后LF、LF HF、TP显著升高 ,HF、BIS及 95 %SEF未见明显改变。结论　CO2 人工气腹使交感神经活性显著升高而对大脑皮层意识活动影响不大     

Multiple mental tasks classification based on nonlinear parameter of mean period using support vector machines

Mental tusk classification is one of the most important problems in Brain-computer interface. This paper studies the classification of five-class mental tusks. The nonlinear parameter of mean period obtained from frequency domain information was used as features for classification implemented by using the method of SVM （support vector machines）. The averaged classification accuracy of 85. 6% over 7 subjects was achieved for 2-second EEG segments. And the results for EEG segments of 0.5s and 5.0s compared favorably to those of Garrett＇s. The results indicate that the parameter of mean period represents mental tusks well for classification, Furthermore, the method of mean period is less computationally demanding, which indicates its potential use for online BCI systems.     

CLASSIFICATIONS OF EEG SIGNALS FOR MENTAL TASKS USING ADAPTIVE RBF NETWORK

Objective This paper presents classifications of mental tasks based on EEG signals using an adaptive Radial Basis Function (RBF) network with optimal centers and widths for the Brain-Computer Interface (BCI) schemes. Methods Initial centers and widths of the network are selected by a cluster estimation method based on the distribution of the training set. Using a conjugate gradient descent method, they are optimized during training phase according to a regularized error function considering the influence of their changes to output values. Results The optimizing process improves the performance of RBF network, and its best cognition rate of three task pairs over four subjects achieves 87.0%. Moreover, this network runs fast due to the fewer hidden layer neurons. Conclusion The adaptive RBF network with optimal centers and widths has high recognition rate and runs fast. It may be a promising classifier for on-line BCI scheme.     

多发性腔隙性脑梗塞的EEG、BEAM、CT/MRI对比分析

对54例经颅脑CT(X线电予计算机断层扫描)或MRI(核磁共振成象)检查确诊为多发性腔隙性脑梗塞病人的EEG(脑电图)、BEAM(脑电地形图)检查结果进行了对比分析。结果表明,BEAM在定位价值上逊于CT或MRI,优于EEG(P<0.01),反映脑功能变化的敏感性方面,BEAM也优于EEG(P<0.05)。BEAM的改变以慢波频段能量增高明显,其分布部位以额颠部最明显,枕颠及额区次之(P<0.05)。认为BEAM对于多发性腔隙性脑梗塞病人不失为一种敏感性较高、对病人无损伤、价廉、易普及的早期辅助检查方法。