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1、[AmarKachenoura,LaurentAlbera,LotfiSenhadji,andPierreComon]©STOCKBYTE&DIGITALVISIONICA:APotentialToolforBCISystems©PHOTOCREDIT[Anin-depthlook]everalstudiesdealingwithindependentcomponentanalysis(ICA)-basedbrain-com-puterinterface(BCI)systemshavebeenreported.Mostofthemhaveonlyexploredalimitednu
2、mberofICAmethods,mainlyFastICAandINFOMAX.TheaimofthisarticleistohelptheBCIcommunityresearchers,especiallythosewhoarenotfamiliarwithSICAtechniques,tochooseanappropriateICAmethod.Forthispurpose,theconceptofICAisreviewedanddifferentmeasuresofstatisticalindependencearereported.Then,theapplica-tion
3、ofthesemeasuresisillustratedthroughabriefdescriptionofthewidelyusedalgorithmsintheICAcommunity,namelySOBI,COM2,JADE,ICAR,FastICA,andINFOMAX.Theimplementa-tionofthesetechniquesintheBCIfieldisalsoexplained.Finally,acomparativestudyofthesealgorithms,conductedonsimulatedelectroencephalography(EEG)
4、data,showsthatanappropri-ateselectionofanICAalgorithmmaysignificantlyimprovethecapabilitiesofBCIsystems.DigitalObjectIdentifier10.1109/MSP.2008.XXXXXXDigitalObjectIdentifier10.1109/MSP.2007.9095301053-5888/08/$25.00©2008IEEEIEEESIGNALPROCESSINGMAGAZINE[57]JANUARY2008INTRODUCTIONextractingsigni
5、ficantfeaturesarecrucialinthedevelopmentofBCItechnologyisaresearchfieldthathasemergedandgrownpracticalBCIsystems.ICA[14]isoneofthepopularsignalpro-rapidlyoverthepast15years(see[8],[31],and[44]foracessingtools,whichhasbeenwidelystudiedduringthelastreview).TheBCIsystemisasetofsensorsandsignalpro
6、cessingtwentyyears.Indeed,agreatnumberofalgorithmsisavailablecomponentsthatallowsacquiringandanalyzingbrainactivitiesandICAreceivedabroadattentioninvariousfieldssuchasbio-withthegoalofestablishingareliablecommunicationchannelmedicalsignalanalysisandprocessing[33],imagerecognitiondirectlybetwee
7、nthebrainandanexternaldevicesuchasacom-[18]andwirelesscommunications[20].Thisarticlefocusesonputer,neuroprosthesis,etc.Moreprecisely,thebasicdesignandtheuseofICAinBCIsystems.SeveralstudiesdealingwithICA-functioningofanyBCIsystemaredepic
