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Ocular artifacts removal from EEG using EMD

Looney, David, Li, Ling, Rutkowski, Tomasz M., Mandic, Danilo P., Cichocki, Andrzej (2008) Ocular artifacts removal from EEG using EMD. In: Wang, Rubin and Shen, Enhua and Gu, Fanji, eds. Proceedings of the International Conference on Cognitive Neurodynamics. ICCN 2007 Proceedings. Proceedings of the International Conference on Cognitive Neurodynamics. ICCN 2007 Proceedings. . pp. 831-835. Springer, Dordecht, Netherlands ISBN 978-1-4020-8386-0. E-ISBN 978-1-4020-8387-7. (doi:10.1007/978-1-4020-8387-7_145) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:49597)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1007/978-1-4020-8387-7_145

Abstract

Electroencephalogram (EEG) provides a non-invasive way to analyze brain activity. Blinking and movement of the eyes causes a strong electrical activity that can contaminate EEG recordings, particularly around the forehead but also as far as in occipital areas. Removal of such ocular artifacts is a considerable signal processing problem, since those artifacts overlap in frequency domain with EEG. In this paper we propose a signal reconstruction method based on a time frequency analysis tool known as the Hilbert-Huang spectrum. We demonstrate how our reconstruction scheme can be successfully applied to contaminated EEG data for the purposes of removing unwanted ocular artifacts.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1007/978-1-4020-8387-7_145
Uncontrolled keywords: Empirical Mode Decomposition; Instantaneous Frequency; Intrinsic Mode Function; Ocular Artifact; Hilbert Spectrum
Subjects: Q Science
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Caroline Li
Date Deposited: 17 Jul 2015 16:37 UTC
Last Modified: 16 Nov 2021 10:20 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/49597 (The current URI for this page, for reference purposes)

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