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Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

2019

Theses/Dissertations

Signal processing

Electronic Thesis and Dissertation Repository

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Full-Text Articles in Engineering

Schrödinger Filtering: A Novel Technique For Removing Gradient Artifact From Electroencephalography Data Acquired During Functional Magnetic Resonance Imaging, Gabriel Bruno Benigno Sep 2019

Schrödinger Filtering: A Novel Technique For Removing Gradient Artifact From Electroencephalography Data Acquired During Functional Magnetic Resonance Imaging, Gabriel Bruno Benigno

Electronic Thesis and Dissertation Repository

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are complementary modalities commonly acquired simultaneously to study brain function with high spatial and temporal resolution. The time-varying gradient fields from fMRI induce massive-amplitude artifacts (GRAs) that overlap in time and frequency with EEG, making GRA removal a challenge for which no satisfactory solution yet exists. We present a new GRA removal method termed Schrödinger filtering (SF). SF is based on semi-classical signal analysis in which a signal is decomposed into a series of energy-based components using the discrete spectrum of the Schrödinger operator. Using a publicly available dataset, we compared our …