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  • Research Article
  • Open Access

Univariate and Bivariate Empirical Mode Decomposition for Postural Stability Analysis

  • 1Email author,
  • 1,
  • 1 and
  • 1
EURASIP Journal on Advances in Signal Processing20082008:657391

  • Received: 22 October 2007
  • Accepted: 7 February 2008
  • Published:


The aim of this paper was to compare empirical mode decomposition (EMD) and two new extended methods of EMD 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.


  • Information Technology
  • Stability Analysis
  • Quantum Information
  • Postural Stability
  • Empirical Mode Decomposition

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Authors’ Affiliations

Charles Delaunay Institute, FRE CNRS 2848, University of Technology of Troyes, 10000 Troyes, France


© Hassan Amoud et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.