基于事件相关电位的脑机接口研究

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1、北京交通大学硕士学位论文基于事件相关电位的脑机接口研究姓名：邓万昌申请学位级别：硕士专业：计算机软件与理论指导教师：王瑞平20081201ABSTRACTABS’l’KAC’I。：Brain-ComputerInterface(BCI)isadirectinformationcommunicationandcontrolchannelestablishedbetweenhumanandcomputerorotherelectricaldevicesanditisawhollynewcommunicationsystemthatdoesnotdependonthebrain’Snormalout

2、putpathwaysofperipheralnervesandmuscles．EEG—BasedBCImayprovidethose‘locked．in’butwithintactideation,withaneffectivecommunicationandcontrolchannelswithoutsideworld．That’SwhyBCIiswinningmoreandmoreattentions．ThewholeBCISystemconstitutesofSignalacquisitionandpre-processing，featureextractionandclassifyi

3、ngalgorithm，outputofcontrollingsignal．AtFirst，theneurologicalbasisofEEGisgenerallysummrized，especiallyforthecharacteristicsofevent-relatedpotentials．ThenitshowsthepartsoftheBCISystemandtheiraims，usualmethods．Secondly,asthe2003globalBCIcompetitiongavethecompetitierstwoproblemaboutEvent-relatedPotenti

4、alwhichrequestthemtostudyprocessingandanalyzingthesignaldata,Ihavedonesomeresearchontheaspectsofpre-processing,featureextractionandclassifyingalgorithm．ThemajorcharacteristicsofP300Signalisthatthelargerpositivewavewillbeseenafter310mswhenthetargetstimulusaccul晤．Inunnoisyevirionment，thepositivewavere

5、achesthemaxmimumafterthetargetstimulusaccurs．IntheP300signalprocessing,thesamplesofeveryleReraftertargetstimulusornontargetstimulusaccursaregatheredanddenoisedbyaddingthesesignaldata．ToSpeeduptheanalyzing，differentmethodsareusedtoignorethosechannelswhichhaveliRleP300elementandimposeliRlecontribution

6、ontheclassifyingresults．Finnally，thepotentialofusefulchannelsissampled，whichconstitutesoffeaturevector,tobeclassifiedwithsupportvectormachineandthecorrectclassifyingrateisuptoPercent87．24．111eelementsofmRandbetarhythmamongtheevokedpotentialarecausedbyimaginglefthandmovingortonguemoving,buttheyhavedi

7、fferentPowerspectrum,frequencyandmoreusefulchannels．Sowechoosethesemoreusefulchannelsaccordingtoevent-ralateddesynchronizationphenomenonandthencountthepowervalueofdifferentfrequencyofthesechannels．Wep