Literature DB >> 27776270

Validity and sensitivity of the longitudinal asymmetry index to detect gait asymmetry using Microsoft Kinect data.

E Auvinet1, F Multon2, V Manning3, J Meunier4, J P Cobb3.   

Abstract

Gait asymmetry information is a key point in disease screening and follow-up. Constant Relative Phase (CRP) has been used to quantify within-stride asymmetry index, which requires noise-free and accurate motion capture, which is difficult to obtain in clinical settings. This study explores a new index, the Longitudinal Asymmetry Index (ILong) which is derived using data from a low-cost depth camera (Kinect). ILong is based on depth images averaged over several gait cycles, rather than derived joint positions or angles. This study aims to evaluate (1) the validity of CRP computed with Kinect, (2) the validity and sensitivity of ILong for measuring gait asymmetry based solely on data provided by a depth camera, (3) the clinical applicability of a posteriorly mounted camera system to avoid occlusion caused by the standard front-fitted treadmill consoles and (4) the number of strides needed to reliably calculate ILong. The gait of 15 subjects was recorded concurrently with a marker-based system (MBS) and Kinect, and asymmetry was artificially reproduced by introducing a 5cm sole attached to one foot. CRP computed with Kinect was not reliable. ILong detected this disturbed gait reliably and could be computed from a posteriorly placed Kinect without loss of validity. A minimum of five strides was needed to achieve a correlation coefficient of 0.9 between standard MBS and low-cost depth camera based ILong. ILong provides a clinically pragmatic method for measuring gait asymmetry, with application for improved patient care through enhanced disease, screening, diagnosis and monitoring. Copyright Â
© 2016. Published by Elsevier B.V.

Entities:  

Keywords:  CRP; Gait analysis; Gait asymmetry; Kinect; Sensitivity analysis

Mesh:

Year:  2016        PMID: 27776270     DOI: 10.1016/j.gaitpost.2016.08.022

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  4 in total

1.  An Automatic Gait Feature Extraction Method for Identifying Gait Asymmetry Using Wearable Sensors.

Authors:  Arif Reza Anwary; Hongnian Yu; Michael Vassallo
Journal:  Sensors (Basel)       Date:  2018-02-24       Impact factor: 3.576

2.  Investigating the impact of a motion capture system on Microsoft Kinect v2 recordings: A caution for using the technologies together.

Authors:  MReza Naeemabadi; Birthe Dinesen; Ole Kæseler Andersen; John Hansen
Journal:  PLoS One       Date:  2018-09-14       Impact factor: 3.240

3.  Agreement Between Spatiotemporal Gait Parameters Measured by a Markerless Motion Capture System and Two Reference Systems-a Treadmill-Based Photoelectric Cell and High-Speed Video Analyses: Comparative Study.

Authors:  Felipe García-Pinillos; Diego Jaén-Carrillo; Victor Soto Hermoso; Pedro Latorre Román; Pedro Delgado; Antonio Carton; Cristian Martinez; Luis Roche Seruendo
Journal:  JMIR Mhealth Uhealth       Date:  2020-10-23       Impact factor: 4.773

4.  Kinect V2-Based Gait Analysis for Children with Cerebral Palsy: Validity and Reliability of Spatial Margin of Stability and Spatiotemporal Variables.

Authors:  Yunru Ma; Kumar Mithraratne; Nichola Wilson; Yanxin Zhang; Xiangbin Wang
Journal:  Sensors (Basel)       Date:  2021-03-17       Impact factor: 3.576

  4 in total

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