Inertial sensor based post fall analysis for false alarming reduction

Lin Ye, Kai Cao, Jay Guo, Xiaojing Huang, Peter Beadle, Ahmadreza Argha, Massimo Piccardi, Guangquan Zhang, Steven W. Su

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

Abstract

One of the major public health problems among elderly people is falling injury. This study investigates fall detection and prevention by using inertial sensors for which the major existing challenging is how to significantly reduce false alarming in order to enhance the acceptance of elderly users during rehabilitation and daily exercises. Different from most existing approaches in the literature, the behavior after falling will be analyzed in details, which can not only greatly reduce false alarming, but also significantly improves the accuracy of the assessment of the severity of falling injuries.

Original languageEnglish
Title of host publicationProceedings of the Third IASTED International Conference on Telehealth and Assistive Technology (TAT 2016)
EditorsM. H. Hamza
Place of PublicationCalgary, Canada
PublisherACTA Press
Pages36-43
Number of pages8
ISBN (Print)9780889869868
DOIs
Publication statusPublished - 17 Oct 2016
Externally publishedYes
EventIASTED International Conference on Telehealth and Assistive Technology (3rd : 2016) - Zurich, Switzerland
Duration: 6 Oct 20168 Oct 2016

Other

OtherIASTED International Conference on Telehealth and Assistive Technology (3rd : 2016)
Abbreviated titleTAT 2016
CountrySwitzerland
CityZurich
Period6/10/168/10/16

Keywords

  • Fall detection
  • Inertial sensor
  • Post fall behavior

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