简介: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.
简介:摘要作者根据项目教学法的理论和课程情况,在“数字视频编辑”课程中设计了13个创意项目,并创设了项目活动情境的教学过程。在教师的引导下,学生以小组为单位自主学习、自主操作完成项目,通过项目评价实现了再认识、再实践的过程,加强了团队意识,提高了实践学习能力,同时培养和激发了学生的艺术创造力。
简介:Thecombinationofelectroencephalogram(EEG)andfunctionalmagneticresonanceimaging(fMRI)isaveryattractiveaiminneuroscienceinordertoachievebothhightemporalandspatialresolutionforthenon-invasivestudyofcognitivebrainfunction.Inthispaper,werecordsimultaneousEEG-fMRIofthesamesubjectinemotionalprocessingexperimentinordertoexplorethecharacteristicsofdifferentemotionalpictureprocessing,andtrytofindthedifferenceofthesubjects’brainhemispherewhileviewingdifferentvalenceemotionalpictures.Thelatepositivepotential(LPP)isareliableelectrophysiologicalindexofemotionalperceptioninhumans.Accordingtotheanalysisresults,theslow-waveLPPandvisualcorticalbloodoxygenlevel-dependent(BOLD)signalsarebothmodulatedbytheratedintensityofpicturearousal.TheamplitudeoftheLPPcorrelatesignificantlywithBOLDintensityinvisualcortex,amygdala,temporalarea,prefrontalandcentralareasacrosspicturecontents.
简介:InordertoexplorethecorrelationbetweentheadjacentsegmentsofalongtermEEG,animprovedprincipalcomponentanalysis(PCA)methodbasedonmutualinformationalgorithmisproposed.Aone-dimensionEEGtimeseriesisdividedequallyintomanysegments,sothateachsegmentcanberegardedasanindependentvariablesandmulti-segmentedEEGcanbeexpressedasadatamatrix.Then,wesubstitutemutualinformationmatrixforcovariancematrixinPCAandconducttherelevanceanalysisofsegmentedEEG.Theexperimentalresultsshowthatthecontributionrateoffirstprincipalcomponent(FPC)ofsegmentedEEGismorelargerthanothers,whichcaneffectivelyreflectthedifferenceofepilepticEEGandnormalEEGwiththechangeofsegmentnumber.Inaddition,theevolutionofFPCconducetoidentifythetime-segmentlocationsofabnormaldynamicprocessesofbrainactivities,theseconclusionsarehelpfulfortheclinicalanalysisofEEG.
简介:BackgroundRightbundlebranchblock(RBBB)maypresentasslurredornotchedSwaveinleadV1.However,slurredornotchedSwavemayalsorepresentslowconductioninthemyocardium.MethodsWeretrospectivelyanalyzedtheQRSpatternsinleadsV3RtoV5Rin7patientswithaslurredornotchedSwaveinleadV1.ResultsIntheleadsV3RtoV5R,6patientsshowedincompleteorcompleteRBBBand1patientslurredornotchedSwave.ConclusionsInthemajorityofECGsinasmallpatientserieswithslurredornotchedSwaveinleadV1,QRSmorphologyindicatingincompleteorcompleteRBBBwaspresentinleadsV3RtoV5R.AfindingoffragmentedQRSintheseleadsmayindicateslowconductioninthemyocardium.
简介:单次脑电分类实验中,采用基于logistic回归的正则化方法来提高分类准确率.首先,提出一种新算法——局部保持投影稀疏logistic回归,将局部保持投影正则项加入到稀疏logistic回归中.该算法旨在保留原始特征空间邻域信息的同时保证结果的稀疏性.然后,利用边界优化法和逐分量迭代算法在训练集上求解权重向量,克服了牛顿一拉夫森法和迭代重加权最小二乘法的局限性.最后,在自步调手指运动数据集上采用十重交叉验证法得到80%的分类准确率,并与稀疏logistic回归的实验结果进行对比,说明局部保持投影正则项有效地保留了对脑电分类有用的信息.