Original title: Reference Signals In Intracranial Eeg: Implementation And Analysis
Authors: Uher, Daniel
Document type: Papers
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: The idea of an artifact-free brain activity recording has been circling around the scientific world for a few decades. Noise present in brain activity recordings may complicate the process of evaluation and interpretation. For the elimination of such unwanted components, the concept of virtual reference signals is usually used. In this work, the algorithms for reference signal estimation using common average-based method as well as more recent methods based on independent component analysis (ICA) were realized and evaluated on a new set of real clinical data. It was found that the ICA-based algorithms allow obtaining more accurate estimation of the reference signal as compared to the average-based one. Finally, all the methods were implemented into a free installable Python toolbox, which will be publicly available after additional testing on real data.
Keywords: average; correlation; ICA; intracranial EEG; reference; Reference signals
Host item entry: Proceedings of the 24th Conference STUDENT EEICT 2018, ISBN 978-80-214-5614-3

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/138183

Permalink: http://www.nusl.cz/ntk/nusl-393369


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