Hilbert-Huang Spectrum as a new field for the identification of EEG event related de-/synchronization for BCI applications

Konstantinos I. Panoulas, Leontios J. Hadjileontiadis, Stavros M. Panas

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

10 Scopus citations

Abstract

Brain Computer Interfaces (BCI) usually utilize the suppression of mu-rhythm during actual or imagined motor activity. In order to create a BCI system, a signal processing method is required to extract features upon which the discrimination is based. In this article, the Empirical Mode Decomposition along with the Hilbert-Huang Spectrum (HHS) is found to contain the necessary information to be considered as an input to a discriminator. Also, since the HHS defines amplitude and instantaneous frequency for each sample, it can be used for an online BCI system. Experimental results when the HHS applied to EEG signals from an on-line database (BCI Competition III) show the potentiality of the proposed analysis to capture the imagined motor activity, contributing to a more enhanced BCI performance.

Original languageBritish English
Title of host publicationProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
PublisherIEEE Computer Society
Pages3832-3835
Number of pages4
ISBN (Print)9781424418152
DOIs
StatePublished - 2008
Event30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada
Duration: 20 Aug 200825 Aug 2008

Publication series

NameProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"

Conference

Conference30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Country/TerritoryCanada
CityVancouver, BC
Period20/08/0825/08/08

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