Koherencija kao značajka signala EEG-a za klasifikaciju afektivnih poremećaja

undergraduate thesis

• Title (english): Coherence as an EEG Feature for Classification of Affective Disorders
• Author: Paula Fanton
• Mentor: Mario Cifrek (mentor)
• Committee member: Mario Cifrek (predsjednik povjerenstva)
• Committee member: Eda Jovičić (član povjerenstva)
• Committee member: Luka Klaić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2024-02-05, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

U ovom radu analizira se baza podataka signala EEG-a s označenim dijagnozama afektivnih poremećaja. Cilj je klasificirati EEG podatke na temelju značajki koherencije kao mjere funkcionalne povezanosti neurona. Na početku rada teoretski su objašnjeni afektivni poremećaji, EEG i predobradba signala. Potom su objašnjene značajke koherecije i postupak izdvajanja značajki. Slijedi objašnjenje metoda strojnog učenja. Na kraju je proveden postupak klasifikacije EEG snimki metodama strojnog učenja na temelju izdvojenih značajki.

Abstract (english)

This paper analyses a database of EEG signals with labelled diagnoses of affective disorders. The aim is to classify EEG data based on coherence features as a measure of functional connectivity between neurons. The paper begins with a theoretical explanation of affective disorders, EEG, and signal preprocessing. Then, coherence features and the feature extraction process are explained. Next, machine learning methods are described. Finally, a classification procedure of EEG recordings using machine learning methods based on the extracted features is conducted.

• Keywords: EEG; afektivni poremećaji; strojno učenje; koherencija
• Keywords (english): EEG; affective disorders; machine learning; coherence
• Language: croatian
• URN:NBN: urn:nbn:hr:168:119494
• Study programme: Title: Computing; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Repository: FER Repository
• Created on: 2024-03-28 07:46:14