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

L. Iuppariello, G. D'Addio, G. Pagano, A. Biancardi, M. Romano, P. Bifulco, M. Cesarelli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publication2016 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467391726
DOIs
Publication statusPublished - Aug 4 2016
Event11th IEEE International Symposium on Medical Measurements and Applications, MeMeA 2016 - Benevento, Italy
Duration: May 15 2016May 18 2016

Other

Other11th IEEE International Symposium on Medical Measurements and Applications, MeMeA 2016
CountryItaly
CityBenevento
Period5/15/165/18/16

Keywords

  • Center of pressure
  • e-textile
  • fourier analysis
  • power spectral density
  • Sensoria
  • sway
  • wavelet analysis

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Instrumentation

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