On the synchrony of empirical mode decompositions with application to electroencephalography

Justin Dauwels, Tomasz M. Rutkowski, François Vialatte, Andrzej Cichocki

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

3 Citations (Scopus)

Abstract

A novel approach to measure the interdependence of time series is proposed, based on the alignment ("matching") of their Huang-Hilbert spectra. The method consists of three steps: first, empirical modes are extracted from the signals; those functions carry non-linear and non-stationary components in frequency limited bands. Second, the empirical modes are Hilbert transformed, resulting in very sharply localized ridges in the time-frequency plane; the obtained time-frequency representations are known as Huang-Hilbert spectra. At last, the latter are pairwise aligned by means of the stochastic-event synchrony method (SES), a recently proposed procedure to match pairs of multi-dimensional point processes. The level of similarity of two Huang-Hilbert spectra is quantified by three parameters: timing and frequency jitter of coincident ridges, and fraction of non-coincident ridges. The proposed method is used to detect steady-state visually evoked potentials (SSVEP) in electroencephalography (EEG) signals; numerical results indicate that the method is vastly more sensitive to SSVEP than classical synchrony measures, and therefore, it may prove to be useful in applications such as brain-computer interfaces. Although the paper mostly deals with EEG, the presented synchrony measure may also be applied to other kinds of time series.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages473-476
Number of pages4
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: 31 Mar 20084 Apr 2008

Publication series

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

Conference

Conference2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Country/TerritoryUnited States
CityLas Vegas, NV
Period31/03/084/04/08

Keywords

  • Electroencephalography
  • Hilbert transforms
  • Spectral analysis
  • Synchronization
  • Time-frequency analysis

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