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Journal Articles Gait & Posture Year : 2017

Validity and sensitivity of the Longitudinal Asymmetry Index to detect gait asymmetry using Microsoft Kinect data

Edouard Auvinet
Victoria Manning
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Justin P. Cobb
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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.
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Dates and versions

hal-01359845 , version 1 (05-09-2016)

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Edouard Auvinet, Franck Multon, Victoria Manning, Jean Meunier, Justin P. Cobb. Validity and sensitivity of the Longitudinal Asymmetry Index to detect gait asymmetry using Microsoft Kinect data. Gait & Posture, 2017, 51, pp.162-168. ⟨10.1016/j.gaitpost.2016.08.022⟩. ⟨hal-01359845⟩
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