DBS artifact suppression using a time-frequency domain filter

  • Electroencephalogram (EEG) is a useful tool for brain research. However, during Deep-Brain Stimulation (DBS), there are large artifacts that obscure the physiological EEG signals. In this paper, we aim at suppressing the DBS artifacts by means of a time-frequency-domain filter. As a pre-processing step, Empirical-Mode Decomposition (EMD) is applied to detrend the raw data. The detrended signals are then filtered iteratively until, by visual inspection, the quality is good enough for interpretation. The proposed algorithm is demonstrated by an application to a clinical DBS-EEG data set in resting state and in finger-tapping condition. Moreover, a comparison with a Low-Pass filter (LPF) is provided, by visual inspection and by a quantitative measure.

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Metadaten
Author:Alina Santillan-Guzman, Ulrich Heute, Muthuraman MuthuramanORCiDGND, Ulrich Stephani, Andreas Galka
URN:urn:nbn:de:bvb:384-opus4-1103384
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/110338
ISBN:978-1-4577-0216-7OPAC
Parent Title (English):2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 3-7 July 2013, Osaka, Japan
Publisher:IEEE
Place of publication:Piscataway, NJ
Editor:Yoshitaka Hirooka, Tomomi Ide, Takuya Kishi, Masaru Sugimachi
Type:Conference Proceeding
Language:English
Year of first Publication:2013
Publishing Institution:Universität Augsburg
Release Date:2023/12/21
First Page:4815
Last Page:4818
DOI:https://doi.org/10.1109/embc.2013.6610625
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Professur für Informatik in der Medizintechnik
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht