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.

Highlights

  • Falls are a major problem for the elderly due to the resulting loss of autonomy and subsequent behavior modification related to fear of falling

  • There was a significant difference in AreaCIMF values between groups for all intrinsic mode functions (IMFs) for all three methods (Figure 5)

  • The area was greater for elderly subjects for control subjects. These increases in the values of AreaCIMF are indicative of degradation in the balance due to the effect of age on postural stability

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Summary

Introduction

Falls are a major problem for the elderly due to the resulting loss of autonomy and subsequent behavior modification related to fear of falling. In France alone, the number of deaths attributed annually to falls is estimated to be more than 9000, with a resultant cost in excess of two billion euros [1]. The cost of falls is only going to increase, in line with the increase in the elderly population. Falling is a consequence of a failure in the postural control system due to aging or a specific pathology. Many risk factors have been identified for falls, the most commonly cited including an underlying muscular weakness, a previous fall, as well as balance and gait problems [3]

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