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  • Research Article
  • Open Access

The PARAChute Project: Remote Monitoring of Posture and Gait for Fall Prevention

  • 1Email author,
  • 1,
  • 2,
  • 2,
  • 1,
  • 1,
  • 1,
  • 3,
  • 2 and
  • 4
EURASIP Journal on Advances in Signal Processing20072007:027421

https://doi.org/10.1155/2007/27421

  • Received: 10 March 2006
  • Accepted: 21 February 2007
  • Published:

Abstract

Falls in the elderly are a major public health problem due to both their frequency and their medical and social consequences. In France alone, more than two million people aged over 65 years old fall each year, leading to more than 9 000 deaths, in particular in those over 75 years old (more than 8 000 deaths). This paper describes the PARAChute project, which aims to develop a methodology that will enable the detection of an increased risk of falling in community-dwelling elderly. The methods used for a remote noninvasive assessment for static and dynamic balance assessments and gait analysis are described. The final result of the project has been the development of an algorithm for movement detection during gait and a balance signature extracted from a force plate. A multicentre longitudinal evaluation of balance has commenced in order to validate the methodologies and technologies developed in the project.

Keywords

  • Public Health
  • Health Problem
  • Information Technology
  • Quantum Information
  • Public Health Problem

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Authors’ Affiliations

(1)
Institute Charles Delaunay, FRE CNRS 2848, University of Technology of Troyes, Troyes, 10000, France
(2)
UMR LORIA 7503, Université de Nancy, CNRS-INRIA, Campus Scientifique, BP 239, Vandoeuvre-lès-Nancy, 54506, France
(3)
Faculté de medicine, Institut régional de Réadaptation, 9 Avenue de la Forêt de Haye, BP 184, Vandoeuvre, 54500, France
(4)
Neuromuscular Physiology Laboratory, Institut of Myology, GH Pitié-Salpêtrière, Paris, 75651, France

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Copyright

© David J. Hewson et al. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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