Quantitative estimation of foot-flat and stance phase of gait using foot-worn inertial sensors

Gait Posture. 2013 Feb;37(2):229-34. doi: 10.1016/j.gaitpost.2012.07.012. Epub 2012 Aug 9.

Abstract

Time periods composing stance phase of gait can be clinically meaningful parameters to reveal differences between normal and pathological gait. This study aimed, first, to describe a novel method for detecting stance and inner-stance temporal events based on foot-worn inertial sensors; second, to extract and validate relevant metrics from those events; and third, to investigate their suitability as clinical outcome for gait evaluations. 42 subjects including healthy subjects and patients before and after surgical treatments for ankle osteoarthritis performed 50-m walking trials while wearing foot-worn inertial sensors and pressure insoles as a reference system. Several hypotheses were evaluated to detect heel-strike, toe-strike, heel-off, and toe-off based on kinematic features. Detected events were compared with the reference system on 3193 gait cycles and showed good accuracy and precision. Absolute and relative stance periods, namely loading response, foot-flat, and push-off were then estimated, validated, and compared statistically between populations. Besides significant differences observed in stance duration, the analysis revealed differing tendencies with notably a shorter foot-flat in healthy subjects. The result indicated which features in inertial sensors' signals should be preferred for detecting precisely and accurately temporal events against a reference standard. The system is suitable for clinical evaluations and provides temporal analysis of gait beyond the common swing/stance decomposition, through a quantitative estimation of inner-stance phases such as foot-flat.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Ankle Joint / physiopathology
  • Ankle Joint / surgery
  • Biosensing Techniques / instrumentation*
  • Case-Control Studies
  • Female
  • Foot / physiopathology*
  • Gait / physiology*
  • Humans
  • Male
  • Osteoarthritis / physiopathology
  • Osteoarthritis / surgery
  • Posture / physiology*
  • Statistics, Nonparametric