Author summary There is a growing interest among clinicians and researchers to use novel pose estimation algorithms that automatically track human movement to analyze human gait. Gait analysis is routinely conducted in designated laboratories with specialized equipment. On the other hand, pose estimation relies on digital videos that can be recorded from household devices such as a smartphone. As a result, these new techniques make it possible to move beyond the laboratory and perform gait analysis in other settings such as the home or clinic. Before such techniques are adopted, we identify a critical need for comparing outcome parameters against three-dimensional motion capture and to evaluate how camera viewpoint affect outcome parameters. We used simultaneous motion capture and left- and right-side video recordings of healthy human gait and calculated spatiotemporal gait parameters and lower-limb joint angles. We find that our provided workflow estimates spatiotemporal gait parameters together with hip and knee angles with the accuracy and precision needed to detect changes in the gait pattern. We demonstrate that the position of the participant relative to the camera affect spatial measures such as step length and discuss the limitations posed by the current approach.
Verification of gait analysis method fusing camera-based pose estimation and an IMU sensor in various gait conditions
Human Gait Analysis Using OpenPose
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Bioengineering, Free Full-Text
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Human Gait Analysis Using OpenPose
Sensors, Free Full-Text
Two-dimensional video-based analysis of human gait using pose estimation
Human Gait Analysis Using OpenPose
Frontiers Development of a Robust, Simple, and Affordable Human Gait Analysis System Using Bottom-Up Pose Estimation With a Smartphone Camera
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PDF) Two-dimensional video-based analysis of human gait using pose estimation
Concurrent validity of human pose tracking in video for measuring gait parameters in older adults: a preliminary analysis with multiple trackers, viewing angles, and walking directions, Journal of NeuroEngineering and Rehabilitation