Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8942198 | Medical Engineering & Physics | 2018 | 7 Pages |
Abstract
Microsoft Kinect for Windows v2 is a motion analysis system that features a markerless human pose estimation algorithm. Given its affordability and portability, Kinect v2 has potential for use in biomechanical research and within clinical settings; however, recent studies suggest high inaccuracy of the markerless algorithm compared to marker-based motion capture systems. A novel tracking method was developed using Kinect v2, employing custom-made colored markers and computer vision techniques. The aim of this study was to test the accuracy of this approach relative to a conventional Vicon motion analysis system, performing a Bland-Altman analysis of agreement. Twenty participants were recruited, and markers placed on bony prominences near hip, knee and ankle. Three-dimensional coordinates of the markers were recorded during treadmill walking and running. The limits of agreement (LOA) of marker coordinates were narrower thanâ¯ââ¯10 and 10â¯mm in most conditions, however a negative relationship between accuracy and treadmill speed was observed along Kinect depth direction. LOA of the surrogate knee angles were withinâ¯ââ¯1.8°, 1.7° for flexion in all conditions andâ¯ââ¯2.9°, 1.7° for adduction during fast walking. The proposed methodology exhibited good agreement with a marker-based system over a range of gait speeds and, for this reason, may be useful as low-cost motion analysis tool for selected biomechanical applications.
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Physical Sciences and Engineering
Engineering
Biomedical Engineering
Authors
Alessandro Timmi, Gino Coates, Karine Fortin, David Ackland, Adam L. Bryant, Ian Gordon, Peter Pivonka,