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Meg data analysis of evoked potentials from visual and auditory stimuli

Patsioura Maria

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URIhttp://purl.tuc.gr/dl/dias/70AE3E73-7515-4AB7-AB04-87F05990654D-
Identifierhttps://doi.org/10.26233/heallink.tuc.66517-
Languageen-
Extent1.77 megabytesen
TitleMeg data analysis of evoked potentials from visual and auditory stimulien
TitleΑνάλυση δεδομένων μαγνητοεγκεφαλογραφήματος από πρόκλητα δυναμικά οπτικού και ακουστικού ερεθίσματοςel
CreatorPatsioura Mariaen
CreatorΠατσιουρα Μαριαel
Contributor [Thesis Supervisor]Zervakis Michalisen
Contributor [Thesis Supervisor]Ζερβακης Μιχαληςel
Contributor [Committee Member]Balas Costasen
Contributor [Committee Member]Μπαλας Κωσταςel
Contributor [Committee Member]Mania Aikaterinien
Contributor [Committee Member]Μανια Αικατερινηel
PublisherΠολυτεχνείο Κρήτηςel
PublisherTechnical University of Creteen
Academic UnitTechnical University of Crete::School of Electrical and Computer Engineeringen
Academic UnitΠολυτεχνείο Κρήτης::Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστώνel
Content SummaryMagnetoencephalogram (MEG) is a useful tool towards the direction of understanding of the mechanisms of human brain having been assessed for its superior accuracy over other modalities. The scope of the present study is the extraction of synchronization features using independent component analysis (ICA) on the MEG recording from normal people after being subjected to an experiment that involves exposure to visual and auditory stimulus. The purpose of this diploma thesis is to process MEG data in order to remove artifacts contaminating the brain activity recordings and then to classify the MEG channels in order to categorize the most important ones, that are most involved in the visual and the auditory brain response, into clusters. For the first task, proper filtering procedures, BSS and ICA methods were used. The application of ICA helps to emerge hidden cerebral and non-cerebral activity and the elimination of non-cerebral activity to the independent components. For the clustering purposes, the method that was used is k-means algorithm, with the help of measures like phase lag index (PLI), energy and kurtosis. Finally, a statistical analysis was performed for the extraction of statistical differences between auditory and visual results.en
Type of ItemΔιπλωματική Εργασίαel
Type of ItemDiploma Worken
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2016-09-30-
Date of Publication2016-
SubjectMEGen
SubjectBioinformaticsen
SubjectTelecommunicationsen
Bibliographic CitationMaria Patsioura, "Meg data analysis of evoked potentials from visual and auditory stimuli", Diploma Work, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2016en
Bibliographic CitationΜαρία Πατσιούρα, "Ανάλυση δεδομένων μαγνητοεγκεφαλογραφήματος από πρόκλητα δυναμικά οπτικού και ακουστικού ερεθίσματος", Διπλωματική Εργασία, Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2016el

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