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Univariate and bivariate empirical mode decomposition for postural stability analysis

  • David Hewson
    ,
  • Hassan Amoud
    ,
  • Hichem Snoussi
    ,
  • Jacques Duchêne
  • Université de technologie de Troyes
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Abstract

The aim of this paper was to compare empirical mode decomposition (EMD) and two new extended methods of Open image in new windowEMD named complex empirical mode decomposition (complex-EMD) and bivariate empirical mode decomposition (bivariate-EMD). All methods were used to analyze stabilogram center of pressure (COP) time series. The two new methods are suitable to be applied to complex time series to extract complex intrinsic mode functions (IMFs) before the Hilbert transform is subsequently applied on the IMFs. The trace of the analytic IMF in the complex plane has a circular form, with each IMF having its own rotation frequency. The area of the circle and the average rotation frequency of IMFs represent efficient indicators of the postural stability status of subjects. Experimental results show the effectiveness of these indicators to identify differences in standing posture between groups.

Publication Information

Output type

Research Output:
Contribution to journal
Article
 Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 657391

Journal (Volume, Issue Number)

Eurasip Journal on Advances in Signal Processing (Volume 2008)

Publication milestones

  • Published - 23/03/2008

Publication status

Published - 23/03/2008

ISSN

1687-6172

Publication IDs

  • handle.net: 10547/623451
  • Scopus: 45749152174

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