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Electronics and Telecommunications Research Institute (한국전자통신연구원)
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Gait event detection algorithm based on smart insoles

  • Kim, JeongKyun (School of Computer Software, ICT, University of Science and Technology) ;
  • Bae, Myung-Nam (Intelligent Convergence Research Laboratory, Electronics and Telecommunications Research Institute) ;
  • Lee, Kang Bok (Intelligent Convergence Research Laboratory, Electronics and Telecommunications Research Institute) ;
  • Hong, Sang Gi (School of Computer Software, ICT, University of Science and Technology)
  • Received : 2018.11.19
  • Accepted : 2019.07.05
  • Published : 2020.02.07
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Abstract

Gait analysis is an effective clinical tool across a wide range of applications. Recently, inertial measurement units have been extensively utilized for gait analysis. Effective gait analyses require good estimates of heel-strike and toe-off events. Previous studies have focused on the effective device position and type of triaxis direction to detect gait events. This study proposes an effective heel-strike and toe-off detection algorithm using a smart insole with inertial measurement units. This method detects heel-strike and toe-off events through a time-frequency analysis by limiting the range. To assess its performance, gait data for seven healthy male subjects during walking and running were acquired. The proposed heel-strike and toe-off detection algorithm yielded the largest error of 0.03 seconds for running toe-off events, and an average of 0-0.01 seconds for other gait tests. Novel gait analyses could be conducted without suffering from space limitations because gait parameters such as the cadence, stance phase time, swing phase time, single-support time, and double-support time can all be estimated using the proposed heel-strike and toe-off detection algorithm.

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References

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