Effects of wavelets analysis on power spectral distributions in posturographic signal processing

Abstract

The preservation of stability and body coordination in humans is assured by the correct working of the postural control system. Usually, postural oscillations is measured by the magnitude of center of pressure (CoP) movement over time. The conventional parameters in frequency domain to quantify changes of the CoP dynamics are estimated using Fourier spectral methods. However, considering the non-stationarity of the CoP signals, the Fourier approach, which breaks a time series signal into various sine wave frequency components, is not adapt. Aim of this work is to compare the wavelet decomposition analysis and the Fourier analysis, in measuring the power spectral distribution of the CoP traces, derived by Sensoria fitness (SF) e-textile socks, in three different frequency bands. Although wavelets analysis (WLT) has shown as a better technique than Fourier (FFT) in the resolution of the CoP oscillatory components, the overall spectral power modifications in their principal frequency bands have not yet been described. Particularly, the spectral power has been calculated in bands I (0.02-0.1 Hz), II (0.2-0.3), III (0.3-0.6), in percent values of the total spectral power.