Robusten postopek za odstranjevanje artefaktov iz elektroencefalografskih (EEG) meritev pri sočasnem snemanju s funkcijsko magnetno resonanco (fMR)

Kraljič, Aleksij (author), Bračun, Drago (mentor)

Elektroencefalografija (EEG) in funkcijska magnetna resonanca (fMR) sta neinvazivni metodi za merjenje možganske aktivnosti. EEG ima v nasprotju s fMR zelo visoko časovno ločljivost (več kHz), medtem ko ima fMR višjo prostorsko ločljivost. Sočasno snemanje EEG in fMR tako omogoča natančnejši vpogled v funkcije možganov. Največja slabost sočasnega snemanja EEG in fMR je močna interakcija med njima, saj se v EEG signalih inducirajo močni artefakti zaradi sprememb magnetnega pretoka. Predstavili smo robusten postopek in algoritme za odstranjevanje tovrstnih artefaktov iz EEG signalov. Z analizo učinkovitosti algoritmov smo dokazali ustrezno odstranitev artefaktov za nadaljnje analize.

• Language: Slovenian
• Keywords: EEG, fMR, nevroznanost, digitalno procesiranje signalov, digitalno filtriranje, splošni linearni model
• Work type: Master's thesis/paper
• Typology: 2.09 - Master's Thesis
• Organization: FS - Faculty of Mechanical Engineering
• Place of publishing: Ljubljana
• Publisher: [A. Kraljič]
• Year: 2019
• Number of pages: XXV, 76 str.
• PID: 20.500.12556/RUL-107581
• UDC: 616.831-073-71(043.2)
• COBISS.SI-ID: 16611355
• Publication date in RUL: 27.04.2019

Secondary language

• Language: English
• Title: Robust procedure for artifact removal from electroencephalographic (EEG) measurements acquired during simultaneous functional magnetic resonance imaging (fMRI)

Abstract

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are noninvasive methods for measuring brain activity. EEG provides a very high temporal resolution, whereas fMRI provides high spatial resolution. A deeper insight into brain functions can be achieved by scanning the brain activity with simultaneous EEG-fMRI. The main downside of simultaneous EEG-fMRI scanning is a high EEG signal contamination caused by electromagnetic induction due to changes in magnetic flux. We presented a robust procedure and algorithms for artifact removal from EEG signal. We analyzed the performance of the procedure and showed a satisfactory artifact reduction for further analyses.

• Keywords: EEG, fMRI, neuroscience, digital signal processing, digital filtering, general linear model