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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
EN
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EL
| URI | http://purl.tuc.gr/dl/dias/70AE3E73-7515-4AB7-AB04-87F05990654D | - |
| Identifier | https://doi.org/10.26233/heallink.tuc.66517 | - |
| Language | en | - |
| Extent | 1.77 megabytes | en |
| Title | Meg data analysis of evoked potentials from visual and auditory stimuli | en |
| Title | Ανάλυση δεδομένων μαγνητοεγκεφαλογραφήματος από πρόκλητα δυναμικά οπτικού και ακουστικού ερεθίσματος | el |
| Creator | Patsioura Maria | en |
| Creator | Πατσιουρα Μαρια | el |
| Contributor [Thesis Supervisor] | Zervakis Michalis | en |
| Contributor [Thesis Supervisor] | Ζερβακης Μιχαλης | el |
| Contributor [Committee Member] | Balas Costas | en |
| Contributor [Committee Member] | Μπαλας Κωστας | el |
| Contributor [Committee Member] | Mania Aikaterini | en |
| Contributor [Committee Member] | Μανια Αικατερινη | el |
| Publisher | Πολυτεχνείο Κρήτης | el |
| Publisher | Technical University of Crete | en |
| Academic Unit | Technical University of Crete::School of Electrical and Computer Engineering | en |
| Academic Unit | Πολυτεχνείο Κρήτης::Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών | el |
| Content Summary | Magnetoencephalogram (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 Item | Διπλωματική Εργασία | el |
| Type of Item | Diploma Work | en |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2016-09-30 | - |
| Date of Publication | 2016 | - |
| Subject | MEG | en |
| Subject | Bioinformatics | en |
| Subject | Telecommunications | en |
| Bibliographic Citation | Maria 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, 2016 | en |
| Bibliographic Citation | Μαρία Πατσιούρα, "Ανάλυση δεδομένων μαγνητοεγκεφαλογραφήματος από πρόκλητα δυναμικά οπτικού και ακουστικού ερεθίσματος", Διπλωματική Εργασία, Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2016 | el |
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