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dc.contributor.advisorIstefanopulos, Yorgo
dc.contributor.advisorGülçür, Halil Özcan
dc.contributor.authorAdemoğlu, Ahmet
dc.date.accessioned2020-12-23T10:41:24Z
dc.date.available2020-12-23T10:41:24Z
dc.date.submitted1995
dc.date.issued2018-08-06
dc.identifier.urihttps://acikbilim.yok.gov.tr/handle/20.500.12812/327516
dc.description.abstractTwo new modeling techniques, based on the damped sinusoids and the wavelet basis,functions, are proposed for the analysis and investigation of Evoked Potentials (EP). Thedamped sinusoid modeling is applied to the averaged and the single trial EPs and therelation between the spontaneous brain electrical activity called Electroencephalogram(EEG) and EP is observed as a phase reordering and amplitude enhancement of certaindamped oscillations. The method which estimates the single trial EP in EEG, allows fortracing the single trial variabilities of the EPs during a recording session. The wavelettransform is applied to the averaged and single trial EPs for the time-frequency analysisof the oscillations occuring in different frequency bands of spontaneous EEG. The relationbetween EEG and EP activity is observed as an amplitude enhancement and a phasealignment of otherwise randomly phased oscillations in the spontaneous BEG. A selectiveaveraging method is proposed based on these findings. The wavelet transform is appliedto the averaged pattern reversal visual EPs collected from normal and Alzheimer's diseasedsubjects. A consistent differentiation of phase behavior in slow oscillations in the deltathetaband (0-7 Hz) is observed between the normal and pathological waveforms.Key words: Electrophysiology, Electroencephalogram, Evoked Potentials, SignalProcessing.en_US
dc.languageEnglish
dc.language.isoen
dc.rightsinfo:eu-repo/semantics/embargoedAccess
dc.rightsAttribution 4.0 United Statestr_TR
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectTıbbi Biyolojitr_TR
dc.subjectMedical Biologyen_US
dc.titleAnalysis of averaged and single evoked potentials using damped sinusoids and wavelet basis functions
dc.typedoctoralThesis
dc.date.updated2018-08-06
dc.contributor.departmentDiğer
dc.identifier.yokid10052612
dc.publisher.instituteBiyo-Medikal Mühendislik Enstitüsü
dc.publisher.universityBOĞAZİÇİ ÜNİVERSİTESİ
dc.identifier.thesisid364494
dc.description.pages106
dc.publisher.disciplineDiğer


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