Univariate and bivariate empirical mode decomposition for postural stability analysis
Affiliation
University of Technology of TroyesIssue Date
2008-03-23Subjects
information technologystability analysis
quantum information
postural stability
empirical mode decomposition
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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.Citation
Amoud H, Snoussi H, Hewson D, Duchêne J (2008) 'Univariate and bivariate empirical mode decomposition for postural stability analysis', EURASIP Journal on Advances in Signal Processing, 2008 (), pp.657391-.Publisher
SpringerAdditional Links
https://link.springer.com/article/10.1155/2008/657391Type
ArticleLanguage
enISSN
1687-6172ae974a485f413a2113503eed53cd6c53
10.1155/2008/657391
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