Validity of a novel method to measure vertical oscillation during running using a depth camera |
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| Affiliation: | 1. Faculty of Kinesiology, University of Calgary, Calgary, Canada;2. Running Injury Clinic, Calgary, Canada;3. Department of Computer Science, University of Calgary, Calgary, Canada;4. Department of Biochemistry & Molecular Biology, University of Calgary, Calgary, Canada;5. Faculty of Nursing, University of Calgary, Calgary, Canada;1. Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Birmingham, UK;2. School of Physiotherapy and Exercise Sciences, Curtin University, GPO Box U1987, Perth, WA 6845, Australia;1. The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy;2. IRCCS Fondazione Don Carlo Gnocchi, Milan, Italy;3. Bertarelli Foundation Chair in Translational NeuroEngineering, Center for Neuroprosthetics and Institute of Bioengineering, School of Engineering, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland;1. Motion Analysis and Biofeedback Laboratory, University of British Columbia, Vancouver, Canada;2. Department of Physical Therapy, University of British Columbia, Vancouver, Canada;3. Graduate Programs in Rehabilitation Sciences, University of British Columbia, Vancouver, Canada;1. Department of Mechanical Engineering, Auburn University, Auburn, AL, United States;2. Department of Education, Auburn University, Auburn, AL, United States |
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| Abstract: | Recent advancements in low-cost depth cameras may provide a clinically accessible alternative to conventional three-dimensional (3D) multi-camera motion capture systems for gait analysis. However, there remains a lack of information on the validity of clinically relevant running gait parameters such as vertical oscillation (VO). The purpose of this study was to assess the validity of measures of VO during running gait using raw depth data, in comparison to a 3D multi-camera motion capture system. Sixteen healthy adults ran on a treadmill at a standard speed of 2.7 m/s. The VO of their running gait was simultaneously collected from raw depth data (Microsoft Kinect v2) and 3D marker data (Vicon multi-camera motion capture system). The agreement between the VO measures obtained from the two systems was assessed using a Bland-Altman plot with 95% limits of agreement (LOA), a Pearson’s correlation coefficient (r), and a Lin’s concordance correlation coefficient (rc). The depth data from the Kinect v2 demonstrated excellent results across all measures of validity (r = 0.97; rc = 0.97; 95% LOA = −8.0 mm – 8.7 mm), with an average absolute error and percent error of 3.7 (2.1) mm and 4.0 (2.0)%, respectively. The findings of this study have demonstrated the ability of a low cost depth camera and a novel tracking method to accurately measure VO in running gait. |
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| Keywords: | Gait analysis Depth sensor Microsoft Kinect Running Vertical oscillation |
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