A 3-channel Active Electrode EEG Device for the Classification of MotorImagery Brain waves for Brain Computer Interface

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dc.contributor.authorBista, Saroj
dc.date.accessioned2022-01-12T06:23:45Z
dc.date.available2022-01-12T06:23:45Z
dc.date.issued2017-11
dc.descriptionThis thesis work presents a cost effective method to record brain wave signals using three channel active electrode EEG device and classify brain waves related to motor imagery(MI) left and right hand movement, based on electroencephalography (EEG) measured from the central lobe ,that could be used for the Brain Computer Interface (BCI) systems.en_US
dc.description.abstractThisthesisworkpresentsacosteffectivemethodtorecordbrainwavesignalsusing threechannelactiveelectrodeEEGdeviceandclassifybrainwavesrelatedtomotor imagery(MI)leftandrighthandmovement,basedonelectroencephalography(EEG) measuredfromthecentrallobe,thatcouldbeusedfortheBrainComputerInterface (BCI)systems.ThegoalofthisthesisistouseIndependentComponentAnalysis (ICA)fortheremovalofEEGartifacts,andthenextractthebrainwavesfeaturesforMI lefthandandMIrighthandmovementusingWaveletDecomposition(WD).The‘Mor- let’motherwaveletisusedforwaveletdecompositionasitshowsbetterperformance foranalysisofnon-stationarybiomedicalsignalslikeEEG.Thebrainwavefeatureslike MaximumPoweramongalldecompositionlevel(MMP),Frequencycorrespondingto MMP(MAF),andMaximumAmplitudeofthesignalwithMAF(MMA)ischosen astheclassificationfeaturesfortheclassificationofMIbrainwaves.Theclassifica-tionofMIbrainwavesignalsisdoneusingLinearDiscriminantAnalysis(LDA)which showedtheaccuracyof81.6%.Thus,thedesignedthreechannelactiveelectrodeEEG deviceusedshowedgoodperformanceforrecordingEEGsignals.Furthermore,signal preprocessingalgorithmICA,featureextractionmethodWaveletDecomposition,and classificationmethodLDAshowedgoodperformancefortheclassificationofMIleft handandMIrighthandactivities.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14540/7294
dc.language.isoenen_US
dc.publisherPulchowk Campusen_US
dc.subjectLDAen_US
dc.subjectMorleten_US
dc.subjectWavelet Decompositionen_US
dc.subjectICAen_US
dc.titleA 3-channel Active Electrode EEG Device for the Classification of MotorImagery Brain waves for Brain Computer Interfaceen_US
dc.typeThesisen_US
local.academic.levelMastersen_US
local.affiliatedinstitute.titlePulchowk Campusen_US
local.institute.titleInstitute of Engineeringen_US
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