Clinical gait analysis using video-based pose estimation: Multiple perspectives, clinical populations, and measuring change
Fig 2
Diagram of frontal plane analysis to obtain spatiotemporal gait parameters.
A person of size (height) s stands at two distances from a frontal plane camera (CFront; panel A): an initial reference depth (dRef) and at a depth-change (Δdi). The size in pixels of the person at each depth are denoted by sRef and si. From trigonometric relationships we derive a relationship between pixel size and depth-change (B, see Methods for detailed explanation; f, focal length of camera; xIP, position of image plane of camera; xCam, position of camera lens; xRef, initial position of person; xi, position of person following depth-change). The predicted pixel sizes of a person standing at increasing depths closely tracks manually annotated pixel sizes, which shows that we can use pixel size to estimate depth-changes (C). Summary of our frontal plane workflow (D): OpenPose tracks anatomical keypoints, we find gait cycle events, calculate a time-series of pixel size, and calculate depth-change at which point step lengths and step times can be derived.