Application of multivariate empirical mode decomposition for cleaning eye blinks artifacts from EEG signals

Esteve Gallego-Jutglà, Jordi Solé-Casals, Tomasz M. Rutkowski, Andrzej Cichocki

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

7 Citations (Scopus)

Abstract

Eye movements and eye blinks are present in most of the electroencephalography (EEG) recordings, making it difficult to interpret or analyze the data. In this paper an extension of empirical mode decomposition (EMD) is proposed in order to clean EEG data of eye blinks artifacts. This is achieved by applying two cleaning methods to EEG simulated data. One of these methods is presented only for illustrative purposes, whereas the second one can be applied to real EEG data. The results show that the cleaned data with both these methods presents high correlation (|r| > 0.8) with the simulated EEG clean data.

Original languageEnglish
Title of host publicationNCTA 2011 - Proceedings of the International Conference on Neural Computation Theory and Applications
Pages455-460
Number of pages6
Publication statusPublished - 2011
Externally publishedYes
EventInternational Conference on Neural Computation Theory and Applications, NCTA 2011 - Paris, France
Duration: 24 Oct 201126 Oct 2011

Publication series

NameNCTA 2011 - Proceedings of the International Conference on Neural Computation Theory and Applications

Conference

ConferenceInternational Conference on Neural Computation Theory and Applications, NCTA 2011
Country/TerritoryFrance
CityParis
Period24/10/1126/10/11

Keywords

  • Artifacts
  • EEG
  • EMD
  • Eye blinks
  • MEMD

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