prikaz prve stranice dokumenta Izdvajanje značajki vidnih evociranih potencijala stabilnog stanja
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undergraduate thesis
Izdvajanje značajki vidnih evociranih potencijala stabilnog stanja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. urn:nbn:hr:168:093339
Jovičić, Eda
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Jovičić, E. (2018). Izdvajanje značajki vidnih evociranih potencijala stabilnog stanja (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:093339

Jovičić, Eda. "Izdvajanje značajki vidnih evociranih potencijala stabilnog stanja." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:093339

Jovičić, Eda. "Izdvajanje značajki vidnih evociranih potencijala stabilnog stanja." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:093339

Jovičić, E. (2018). 'Izdvajanje značajki vidnih evociranih potencijala stabilnog stanja', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 05 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:093339

Jovičić E. Izdvajanje značajki vidnih evociranih potencijala stabilnog stanja [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2018 [cited 2024 July 05] Available at: https://urn.nsk.hr/urn:nbn:hr:168:093339

E. Jovičić, "Izdvajanje značajki vidnih evociranih potencijala stabilnog stanja", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:168:093339

Metadata
TitleIzdvajanje značajki vidnih evociranih potencijala stabilnog stanja
Title (english)Steady State Visual Evoked Potentials Feature Extraction
AuthorEda Jovičić
MentorMario Cifrek (mentor)
Committee memberMario Cifrek (predsjednik povjerenstva)
Committee memberŽeljka Lučev Vasić (član povjerenstva)
Committee memberKrešimir Friganović (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2018-07-13, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Abstract
Ostvarivanje sučelja mozga i računala (engl. Brain-computer interface, BCI) temelji se na mjerenju bioelektrične aktivnosti mozga. U ovom radu promatraju se vidni evocirani potencijali stabilnog stanja (engl. steady state visually evoked potentials, SSVEP) koji se pojavljuju kada osoba prima treptajući svjetlosni podražaj. Evocirani potencijali mjereni su elektroencefalogramom (EEG) na okcipitalnoj regiji mozga. EEG signali obrađeni su brzom Fourierovom transformacijom i kanonskom korelacijskom analizom, te je provedena klasifikacija dobivenih značajki. Obrada se provodila na različitim vremenskim odsječcima signala s ciljem smanjenja potrebne količine podataka za uspješnu klasifikaciju. Uspoređene su točnosti klasificiranja dviju navedenih metoda na različitim vremenskim odsječcima temeljem čega su izdvojene korisne značajke.
Abstract (english)
Creating brain-computer interface (BCI) is based on measuring bioelectric brain activity. This paper observes steady state visually evoked potentials (SSVEP). SSVEP occurs when a person receives flashing light stimulus. SSVEPs were measured by electroencephalogram (EEG) on the occipital region of the brain. EEG signals were processed by Fast Fourier Transformation (FFT) and Canonical Correlation Analysis (CCA) and a classification of the obtained features was performed. The processing was carried out at different time slots of the signal with the goal of reducing required amount of data for a successful classification. We compared the classification accuracy of the two listed methods on different time slots. This was used to select features which are useful for further processing.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:093339
Study programmeTitle: 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 resourceText
File originBorn digital
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Created on2019-03-13 21:14:50