2019
Kobsar, D.; Osis, S. T.; Jacob, Christian; Ferber, Reed
Validity of a novel method to measure vertical oscillation during running using a depth camera Journal Article
In: Journal of Biomechanics, vol. 85, pp. 182-186, 2019.
Abstract | Links | BibTeX | Tags: biomechanics, gait analysis, virtual reality
@article{Kobsar2019,
title = {Validity of a novel method to measure vertical oscillation during running using a depth camera},
author = {D. Kobsar and S.T. Osis and Christian Jacob and Reed Ferber },
doi = {10.1016/j.jbiomech.2019.01.006},
year = {2019},
date = {2019-03-06},
urldate = {2019-03-06},
journal = {Journal of Biomechanics},
volume = {85},
pages = {182-186},
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.},
keywords = {biomechanics, gait analysis, virtual reality},
pubstate = {published},
tppubtype = {article}
}
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.