Longitudinal Falls - Risk Estimation Using Triaxial Accelerometry

  • Narayanan M
  • Redmond S
  • Scalzi M
 et al. 
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Abstract

See, stats, and : https : / / www . researchgate . net / publication / 26855930 Longitudinal - Risk Triaxial Article - medical DOI : 10 . 1109 / TBME . 2009 . 2033038 : PubMed CITATIONS 45 READS 32 6 , including : Some : Studies Multidomain Stephen UNSW 132 , 173 SEE Stephen Neuroscience 535 , 599 SEE B . G . Celler The 211 , 224 SEE Nigel UNSW 484 , 034 SEE All . The . All - text and , letting . Abstract—Falls among the elderly population are a major cause of morbidity and injury—particularly among the over 65 years age group . Validated clinical tests and associated models , built upon assessment of functional ability , have been devised to estimate an individual ' s risk of falling in the near future . Those identified as at - risk of falling may be targeted for interventative treatment . The migration of these clinical models estimating falls risk to a sur - rogate technique , for use in the unsupervised environment , might broaden the reach of falls - risk screening beyond the clinical arena . This study details an approach that characterizes the movements of 68 elderly subjects performing a directed routine of unsupervised physical tasks . The movement characterization is achieved through the use of a triaxial accelerometer . A number of fall - related fea - tures , extracted from the accelerometry signals , combined with a linear least squares model , maps to a clinically validated measure of falls risk with a correlation of ρ = 0 . 81 (p < 0 . 001) .

Author-supplied keywords

  • Index Terms—Accelerometry
  • falls
  • falls risk
  • signal processing

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Authors

  • Michael R Narayanan

  • Stephen J Redmond

  • Maria Elena Scalzi

  • Stephen R Lord

  • Branko G Celler

  • Nigel H Lovell

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