Separation of EOG artifacts from eeg signals using bivariate emd

Md K.I. Molla, T. Tanaka, T. M. Rutkowski, A. Cichocki

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

35 Citations (Scopus)

Abstract

A problem of eye-movement muscular interference removal from EEG recordings is described. In many experiments in neuroscience it is crucial to separate different sources of electrical activity within human body in a situation when a very limited knowledge about nonlinear and nonstationary nature of the mixing process is available. A new two step extension to bivariate empirical mode decomposition is proposed to remove ocular artifacts from EEG with a use of fractional Gaussian noise as a reference first to preprocess EOG signal, which is next used in the second step as a reference to clean EEG signals. Results with EEG experimental data validate the proposed approach.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
Pages562-565
Number of pages4
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, TX, United States
Duration: 14 Mar 201019 Mar 2010

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
Country/TerritoryUnited States
CityDallas, TX
Period14/03/1019/03/10

Keywords

  • Bivariate empirical mode decomposition (BEMD)
  • Electroencephalography
  • Electrooculography
  • Fractional gaussian noise (FGN)

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