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Abstract
BackgroundMany of the available gait monitoring technologies are expensive, require specialized expertise, are time consuming to use, and are not widely available for clinical use. The advent of video-based pose tracking provides an opportunity for inexpensive automated analysis of human walking in older adults using video cameras. However, there is a need to validate gait parameters calculated by these algorithms against gold standard methods for measuring human gait data in this population.MethodsWe compared quantitative gait variables of 11 older adults (mean age = 85.2) calculated from video recordings using three pose trackers (AlphaPose, OpenPose, Detectron) to those calculated from a 3D motion capture system. We performed comparisons for videos captured by two cameras at two different viewing angles, and viewed from the front or back. We also analyzed the data when including gait variables of individual steps of each participant or each participant’s averaged gait variables.ResultsOur findings revealed that, i) temporal (cadence and step time), but not spatial and variability gait measures (step width, estimated margin of stability, coefficient of variation of step time and width), calculated from the video pose tracking algorithms correlate significantly to that of motion capture system, and ii) there are minimal differences between the two camera heights, and walks viewed from the front or back in terms of correlation of gait variables, and iii) gait variables extracted from AlphaPose and Detectron had the highest agreement while OpenPose had the lowest agreement.ConclusionsThere are important opportunities to evaluate models capable of 3D pose estimation in video data, improve the training of pose-tracking algorithms for older adult and clinical populations, and develop video-based 3D pose trackers specifically optimized for quantitative gait measurement.
Highlights
Many of the available gait monitoring technologies are expensive, require specialized expertise, are time consuming to use, and are not widely available for clinical use
The aim of this study was, to investigate the concurrent validity of spatiotemporal gait measurement in the frontal plane based on three common pose trackers (AlphaPose [13], OpenPose [8], and Detectron [14]) against a 3D motion capture system by doing a correlation analysis between the gait variables calculated from the two systems in older adults
We compared the gait variables calculated from 2D videos of standard RGB cameras using three pose tracking algorithms to those calculated from a 3D motion capture system
Summary
Many of the available gait monitoring technologies are expensive, require specialized expertise, are time consuming to use, and are not widely available for clinical use. Established techniques for examining gait quality in older adults typically require technologies such as motion capture systems which are expensive and time consuming, require specialized expertise and staff to operate, and are not widely available for clinical use. With the advent of commercially available depth cameras, the Kinect sensor (Microsoft, Redmond, WA), researchers were able to monitor natural walking of participants [2,3,4,5,6,7]. The Kinect camera has a limited depth of field (0.5 to 4.5 m) which can only capture few steps This limitation, along with concerns about cost and potential hardware obsolescence (the sensor was commercially unavailable for an extended period until a newer version was released) motivate adopting other technologies for the purpose of natural gait monitoring. Other depth sensing cameras are available, it would be ideal if technologies can make use of regular videos from cameras that are ubiquitous, such as surveillance cameras
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