Skip to main navigation Skip to search Skip to main content

Analysis of center of pressure signals using empirical mode decomposition and Fourier-Bessel expansion

  • David Hewson
  • , Ram Bilas Pachori
  • , Hichem Snoussi
  • , Jacques Duchêne

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

24 Citations (Scopus)

Abstract

Center of pressure (COP) measurements are often used to identify balance problems. A new method for analysis of COP signals using empirical mode decomposition (EMD) and Fourier-Bessel (FB) expansion is proposed in this paper. The EMD decomposes a COP signal into a finite set of band-limited signals termed intrinsic mode functions (IMFs), before FB expansion is applied on each IMF to compute mean frequency. The FB expansion based representation is suitable for use in non-stationary and very short duration signals. Seventeen subjects were tested under eyes open (EO) and eyes closed (EC) conditions, with different vibration frequencies applied for EC condition to further perturb sensory information. Mean frequency as calculated by FB expansion for the first three IMFs was able to distinguish between EO and EC conditions (p < 0.05), while only first IMF was able to detect a vibration effect.
Original languageEnglish
Title of host publicationnan
PublisherInstitute of Electrical and Electronics Engineers Inc.
DOIs
Publication statusPublished - 31 Dec 2008
EventTENCON 2008 - 2008 IEEE Region 10 Conference - Hyderabad
Duration: 19 Nov 200821 Nov 2008

Conference

ConferenceTENCON 2008 - 2008 IEEE Region 10 Conference
CityHyderabad
Period19/11/0821/11/08
OtherTENCON 2008 - 2008 IEEE Region 10 Conference (19/11/2008-21/11/2008, Hyderabad)

Keywords

  • Fourier-Bessel expansion
  • centre of pressure
  • empirical mode decomposition
  • intrinsic mode functions
  • pressure signals
  • vibration frequencies

Fingerprint

Dive into the research topics of 'Analysis of center of pressure signals using empirical mode decomposition and Fourier-Bessel expansion'. Together they form a unique fingerprint.

Cite this