title: New lower-limb gait asymmetry indices based on a depth camera.
abstract: BACKGROUND
  Various asymmetry indices have been proposed to compare the spatiotemporal, kinematic and kinetic parameters of lower limbs during the gait cycle. However, these indices rely on gait measurement systems that are costly and generally require manual examination, calibration procedures and the precise placement of sensors/markers on the body of the patient.
  
  
  METHODS
  To overcome these issues, this paper proposes a new asymmetry index, which uses an inexpensive, easy-to-use and markerless depth camera (Microsoft Kinect™) output. This asymmetry index directly uses depth images provided by the Kinect™ without requiring joint localization. It is based on the longitudinal spatial difference between lower-limb movements during the gait cycle. To evaluate the relevance of this index, fifteen healthy subjects were tested on a treadmill walking normally and then via an artificially-induced gait asymmetry with a thick sole placed under one shoe. The gait movement was simultaneously recorded using a Kinect™ placed in front of the subject and a motion capture system.
  
  
  RESULTS
  The proposed longitudinal index distinguished asymmetrical gait (p < 0.001), while other symmetry indices based on spatiotemporal gait parameters failed using such Kinect™ skeleton measurements. Moreover, the correlation coefficient between this index measured by Kinect™ and the ground truth of this index measured by motion capture is 0.968.
  
  
  CONCLUSIONS
  This gait asymmetry index measured with a Kinect™ is low cost, easy to use and is a promising development for clinical gait analysis.
authors.affiliation: University Rennes 2, ENS Rennes, Campus de Ker lann, Avenue Robert Schuman, Bruz 35170, France. edouard.auvinet@polymtl.ca.|Université de Montréal, C.P. 6128, succ. Centre-ville, Montréal H3C 3J7, QC, Canada. edouard.auvinet@polymtl.ca.
authors.forename: Edouard
authors.initials: E
authors.lastname: Auvinet
authors.affiliation: University Rennes 2, ENS Rennes, Campus de Ker lann, Avenue Robert Schuman, Bruz 35170, France. franck.multon@irisa.fr.|Inria, Campus Universitaire de Beaulieu, Rennes 35052, France. franck.multon@irisa.fr.
authors.forename: Franck
authors.initials: F
authors.lastname: Multon
authors.affiliation: Université de Montréal, C.P. 6128, succ. Centre-ville, Montréal H3C 3J7, QC, Canada. meunier@iro.umontreal.ca.
authors.forename: Jean
authors.initials: J
authors.lastname: Meunier
mesh_terms: D001696:Biomechanical Phenomena; D005080:Exercise Test; D005684:Gait / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007700:Kinetics; D035002:Lower Extremity / Q000502:physiology; D009068:Movement / Q000502:physiology; D014741:Video Recording; D016138:Walking / Q000502:physiology*