KE was supported by an AGE-WELL Network of Centres of Excellence in Technology and Aging Graduate Student Award. NS was supported by a Simon Fraser University Graduate Dean’s Entrance Scholarship and a CIHR Community Support Travel Award (164472). This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All relevant data are within the manuscript and its Supporting Information files.įunding: This work was supported by operating grants from the Canadian Institutes of Health Research (funding reference numbers AMG-100487, TIR-103945, and TEI-138295) and the AGE-WELL National Centre for Excellence (AW CRP 2015-WP5.2, AWCRP-2020-04).
Received: ApAccepted: OctoPublished: October 25, 2021Ĭopyright: © 2021 Shishov et al. PLoS ONE 16(10):Įditor: Manabu Sakakibara, Tokai University, JAPAN
#ANGLE TRACKING KINOVEA SOFTWARE#
Lower accuracy was observed for angular kinematics of the upper and lower limb in sideways falls, and for horizontal measures from 30 degree cameras or 1D height-based calibration.Ĭitation: Shishov N, Elabd K, Komisar V, Chong H, Robinovitch SN (2021) Accuracy of Kinovea software in estimating body segment movements during falls captured on standard video: Effects of fall direction, camera perspective and video calibration technique. Our results demonstrate that Kinovea can be applied to 30 Hz video to measure linear positions and velocities to within 9% accuracy. When compared to 10 Hz, filtering at 3 Hz caused velocity errors to increase 1.4-fold. Errors in horizontal velocity were 2.5-fold higher for a 30 than 90 degree camera angle, and 1.6-fold higher for calibration using participants’ height (1D) instead of a 2D grid. Errors in angular measures averaged over 2-fold higher in sideways than forward or backward falls, due to out-of-plane movement of the knees and elbows. For a camera oriented perpendicular to the plane of the fall (90 degrees), Kinovea position data filtered at 10 Hz, and video calibration using a 2D grid, mean root mean square errors were 0.050 m or 9% of the signal amplitude and 0.22 m/s (7%) for vertical position and velocity, and 0.035 m (6%) and 0.16 m/s (7%) for horizontal position and velocity. We also examined how Kinovea accuracy depended on fall direction, camera angle, filtering cut-off frequency, and calibration technique. We examined the validity of this approach by conducting laboratory falling experiments, and comparing linear and angular positions and velocities measured from 3D motion capture to estimates from Kinovea 2D digitization software based on standard surveillance video (30 Hz, 640x480 pixels). Video footage of real-life falls is increasingly available, and may be used with digitization software to extract kinematic features of falls. Understanding the movements of the body during falls is important to the design of fall prevention and management strategies, including exercise programs, mobility aids, fall detectors, protective gear, and safer environments. For both quality depth and tracking, use the D415 and the T265 in parallel.Falls are a major cause of unintentional injuries. ?or some use cases, SLAM on the D435i will be ideal, but for the highest quality tracking, choose the T265. For these reasons, T265 will succeed in many use cases where D400 based SLAM will fail.Īdditionally, when using the T265, no additional resources are required on the platform in terms of compute to perform the SLAM algorithms, which means that tracking with T265 is platform independent, has a low integration cost, and can run on very low compute devices. Furthermore, the T265 is optimized for power and latency using its embedded VPU. As such, a SLAM solution based on the information from a single D400 camera will get lost in certain situations when T265 will not.
#ANGLE TRACKING KINOVEA SERIES#
It is possible to run host-based SLAM using our D400 series depth cameras – ideally the D435i, however these cameras are optimized for depth accuracy at the expense of field of view – D400 cannot see as much of the world as T265. All SLAM solutions, and there are many good ones, are limited by the information they receive.
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