Ανάλυση φάσματος εγκεφαλικών δικτύων σε συνθήκες εγκεφαλικής κόπωσης.

Γκουστοβά, Φωτεινή; Gkoustova, Fotini

dc.contributor.author	Γκουστοβά, Φωτεινή	el
dc.contributor.author	Gkoustova, Fotini	en
dc.date.accessioned	2024-04-22T08:38:24Z
dc.date.available	2024-04-22T08:38:24Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/59235
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.26931
dc.rights	Default License
dc.subject	Ηλεκτροεγκεφαλογράφημα	el
dc.subject	ΗΕΓ	el
dc.subject	Πνευματική Κόπωση	el
dc.subject	Δίκτυα Εγκεφάλου	el
dc.subject	Θεωρία γράφων	el
dc.subject	Ελάχιστο συνεκτικό δέντρο	el
dc.subject	Eeglab	en
dc.subject	PLI	en
dc.subject	MST	en
dc.title	Ανάλυση φάσματος εγκεφαλικών δικτύων σε συνθήκες εγκεφαλικής κόπωσης.	el
heal.type	bachelorThesis
heal.classification	Neuroscience	en
heal.language	el
heal.access	ebargo	el
heal.recordProvider	ntua	el
heal.publicationDate	2023-10
heal.abstract	My thesis focuses on the analysis of electroencephalogram (EEG) connectivity data through a series of calculations in the MATLAB environment. The work requires using functional tools and performing complex calculations to assess the connectivity of the human brain. The main tools used include EEGLAB to process the EEG data and export it in a format suitable for analysis. The work involved loading and preprocessing EEG data, applying filters in various frequency bands (delta, theta, alpha, beta, gamma) to extract frequency components, calculating the Phase Lag Index (PLI), which represents the connectivity between different EEG signals, apply graphical network metrics such as contractility, characteristic path, and microcosm to evaluate network connectivity, save network metrics to files for future analysis and visualization. This work is of great importance in understanding the connectivity of the human brain and can be used in future studies to detect any abnormalities or predict various neurological diseases.	el
heal.advisorName	Ματσόπουλος, Γεώργιος	el
heal.committeeMemberName	Ματσόπουλος, Γεώργιος	el
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών	el
heal.academicPublisherID	ntua
heal.fullTextAvailability	false