Development and evaluation of a prior-to-impact fall event detection algorithm

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Abstract

Automatic fall event detection has attracted research attention recently for its potential application in fall alarming system and wearable fall injury prevention system. Nevertheless, existing fall detection research is facing various limitations. The current study aimed to develop and validate a new fall detection algorithm using 2-D information (i.e., trunk angular velocity and trunk angle). Ten healthy elderly were involved in a laboratory study. Sagittal trunk angular kinematics was measured using inertial measurement unit during slip-induced backward falls and a variety of daily activities. The new algorithm was, on average, able to detect backward falls prior to impact, with 100% sensitivity, 95.65% specificity, and 255 ms response time. Therefore, it was concluded that the new fall detection algorithm was able to effectively detect falls during motion for the elderly population.

Original languageEnglish (US)
Article number6783798
Pages (from-to)2135-2140
Number of pages6
JournalIEEE Transactions on Biomedical Engineering
Volume61
Issue number7
DOIs
StatePublished - Jul 2014
Externally publishedYes

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Keywords

  • Fall detection
  • Fall intervention
  • Slips and falls

ASJC Scopus subject areas

  • Biomedical Engineering

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