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One-class support vector machine for joint variable selection and detection of postural balance degradation

  • David Hewson
  • , Hassan Amoud
  • , Hichem Snoussi
  • , Jacques Duchêne

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

Abstract

The study of the static posture is of great interest for the analysis of the deficit of the control of balance. A method of balance analysis is to use a platform of forces which makes it possible to extract displacement of the centre of pressure (COP). The parameters extracted from COP time series prove like variables keys to supervise the degradation of balance. However, the irrelevance and\or the redundancy of some of them make difficult an effective detection of degradation. The objective of this paper is the implementation of a method of detection (SVDD) and of a procedure of selection of the relevant parameters able to detect a degradation of balance. The selected criterion of selection is the maximization of the area AUC under the curve ROC.
Original languageEnglish
Title of host publicationIFMBE Proceedings
PublisherSpringer
Pages204-207
Volume22
EditionVol 22
DOIs
Publication statusPublished - 31 Dec 2009
Event4th European Conference of the International Federation for Medical and Biological Engineering -
Duration: 31 Dec 2009 → …

Conference

Conference4th European Conference of the International Federation for Medical and Biological Engineering
Period31/12/09 → …
Other4th European Conference of the International Federation for Medical and Biological Engineering

Keywords

  • Detection
  • One Class classification
  • feature selection
  • posture
  • support vector data description

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