Literature DB >> 26718063

Real-time measurement of pelvis and trunk kinematics during treadmill locomotion using a low-cost depth-sensing camera: A concurrent validity study.

Tom W Macpherson1, Jonathan Taylor2, Thomas McBain2, Matthew Weston2, Iain R Spears2.   

Abstract

There is currently no suitable kinematic system for a large-scale prospective trial assessing risk factors of musculoskeletal disorders. A practical kinematic system is described which involves the use of a single low-cost depth-sensing camera for the real-time measurement of 3-dimensional linear and angular pelvic and trunk range-of-movement (ROM). The method is based on the creation and processing of dynamic point clouds taken from the posterior surface of the pelvis and trunk. Nine healthy participants performed 3 trials of treadmill locomotion when walking at self-selected speed (3.6-5.6 km/h), running at 70% (10.9-14.0 km/h) and 90% of maximal speed (14.0-18.0 km/h). Stride-by-stride linear and angular ROM data were captured concurrently using the single depth-sensing camera running at 30 Hz (Kinect(TM) for Windows, Microsoft, USA) and a six-camera motion capture system at 100 Hz (Vicon MX13, Vicon Motion Systems, United Kingdom). Within subject correlation coefficients between the practical and criterion method ranged from very large to nearly perfect (r=0.87-1.00) for the linear ROM. Correlation coefficients for the angular ROM ranged from moderate to very large (r=0.41-0.80). The limits of agreement between the two systems for linear movements were ≤ 9.9 mm at all velocities of gait and ≤ 4.6° at all velocities of gait. The single camera system using depth-sensing technology is capable of capturing linear pelvic and trunk ROM during treadmill locomotion with reasonable precision when compared to the criterion method. Further improvements to the measurement of angles and validation across a wider population are recommended.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Centre of mass; Gait analysis; Kinect; Locomotion analysis; Lumbopelvis; Pelvic oscillations

Mesh:

Year:  2015        PMID: 26718063     DOI: 10.1016/j.jbiomech.2015.12.008

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  6 in total

1.  Experimental Validation of Depth Cameras for the Parameterization of Functional Balance of Patients in Clinical Tests.

Authors:  Francisco-Ángel Moreno; José Antonio Merchán-Baeza; Manuel González-Sánchez; Javier González-Jiménez; Antonio I Cuesta-Vargas
Journal:  Sensors (Basel)       Date:  2017-02-22       Impact factor: 3.576

2.  Barefoot running does not affect simple reaction time: an exploratory study.

Authors:  Nicholas J Snow; Jason F L Blair; Graham Z MacDonald; Jeannette M Byrne; Fabien A Basset
Journal:  PeerJ       Date:  2018-04-09       Impact factor: 2.984

3.  Kinect-based assessment of proximal arm non-use after a stroke.

Authors:  K K A Bakhti; I Laffont; M Muthalib; J Froger; D Mottet
Journal:  J Neuroeng Rehabil       Date:  2018-11-14       Impact factor: 4.262

Review 4.  A SWOT Analysis of Portable and Low-Cost Markerless Motion Capture Systems to Assess Lower-Limb Musculoskeletal Kinematics in Sport.

Authors:  Cortney Armitano-Lago; Dominic Willoughby; Adam W Kiefer
Journal:  Front Sports Act Living       Date:  2022-01-25

Review 5.  Review-Emerging Portable Technologies for Gait Analysis in Neurological Disorders.

Authors:  Christina Salchow-Hömmen; Matej Skrobot; Magdalena C E Jochner; Thomas Schauer; Andrea A Kühn; Nikolaus Wenger
Journal:  Front Hum Neurosci       Date:  2022-02-03       Impact factor: 3.169

6.  Evaluation of the Pose Tracking Performance of the Azure Kinect and Kinect v2 for Gait Analysis in Comparison with a Gold Standard: A Pilot Study.

Authors:  Justin Amadeus Albert; Victor Owolabi; Arnd Gebel; Clemens Markus Brahms; Urs Granacher; Bert Arnrich
Journal:  Sensors (Basel)       Date:  2020-09-08       Impact factor: 3.576

  6 in total

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