Vremensko-frekvencijska transformacija evociranih potencijala pomoću programskog alata ERPWAVELAB

undergraduate thesis

• Title (english): Time-frequency transformation of event-related potentials using the toolbox ERPWAVELAB
• Author: Ivana Storjak
• Mentor: Mario Cifrek (mentor)
• Committee member: Mario Cifrek (predsjednik povjerenstva)
• Committee member: Željka Lučev Vasić (član povjerenstva)
• Committee member: Sara Žulj (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2015-09-07, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Electrical Engineering

Abstract

Neinvazivna metoda mjerenja električne moždane aktivnosti naziva se encefalografija. EEG se temelji na postsinaptičkim potencijalima nastalima zbog sinkronog djelovanja skupine neurona. Nakon podražaja javljaju se karakteristični valovi u odgovarajućim regijama mozga u točno određenom periodu koje nazivamo evociranim potencijalima. Zbog nestacionarnosti signala nije moguće koristiti Fourierovu transformaciju već se koristi STFT ili valićna transformacija. Ograničena vremenska i frekvencijska razlučivost STFT-a nasuprot promjenjive razlučivosti uvjetovane karakteristikama valića čine valićnu transformaciju prigodnom za obradu EEG signala. Analiza evociranih potencijala korištenjem naprednih programskih alata daje bolji uvid u karakteristike signala stoga je za vremensko-frekvencijsku analizu korišten ERPWAVELAB. Karakteristični parametri alata pružaju mogućnost bolje vizualizacije i interpretacije signala pa tako i vala P300 dobivenog primjenom oddball paradigme.

Abstract (english)

Electroencephalography (EEG) is a non-invasive method of measuring electrical brain activity. EEG is based on the postsynaptic potentials that are the result of synchronous oscillatory activity of neurons in the brain. Brain stimulation results in a specific response waves in the relevant regions and in a specific period after the stimuli. Specific response of the brain is called evoked potentials. Due to the non-stationary signals it is not possible to use the Fourier transform but rather STFT or wavelet transform are used. Considering the fact that STFT is defined with limited time and frequency resolution, wavelet transform is more appropriate for processing EEG signals. Analysis of the evoked potentials using advanced programming tools gives better insight into the characteristics of the signal, so ERPWAVELAB tool was used. Tool parameters provide visualization in time-frequency domain and a different insight of P300 obtained by using oddball paradigm.

• Keywords: elektroencefalogram (EEG); evocirani potencijali; P300; valićna transformacija; vremensko-frekvencijska analiza; ERPWAVELAB parametri
• Keywords (english): electroencephalogram (EEG); evoked potentials; P300; wavelet transform; time- frequency analysis; ERPWAVELAB parameters
• Language: croatian
• URN:NBN: urn:nbn:hr:168:951741
• Study programme: Title: Electrical Engineering and Information Technology; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka elektrotehnike i informacijske tehnologije (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka elektrotehnike i informacijske tehnologije)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2018-02-06 12:08:20