Univariate and Bivariate Empirical Mode Decomposition for Postural Stability Analysis. (14th May 2008)

• Record Type: Journal Article
• Authors: Amoud Amoud, Hassan Hassan; Snoussi Snoussi, Hichem Hichem; Hewson Hewson, David David; Duchêne Duchêne, Jacques Jacques
• Other Names: Barner Barner Kenneth Kenneth Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2008(2008)
• Publication Date: 2008-05-14
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2008/657391
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : 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.