To assess the validity of an algorithm that estimates spatiotemporal gait parameters in people with MS (PwMS) using only a single consumer-grade video.

Gait analysis in PwMS typically requires expensive tools, such as motion capture or pressure mats. In contrast, pose estimation software provides a low-cost, accessible method to collect kinematic data. 

153 adult PwMS were recorded with a single consumer-grade camera in the frontal plane while walking as fast as safely possible; among these, videos from a second timepoint were available for 73 participants. Videos were processed using MediaPipe Pose pose estimation software. A custom-written algorithm then calculated the following gait parameters: an estimate of walking speed, stride time, cadence, and stride width. Additionally, Timed-25 Foot Walk (T25FW) was collected.

In a multivariate model, older age (Estimate 0.0048 [0.0019, 0.0078], p=0.002), slower walking speed estimate (-0.26 [-0.33, -0.19], p<0.001), and longer stride time (0.97 [0.75, 1.2], p<0.001) were associated with slower walking by T25FW. These three variables predicted a majority of variance in log-transformed T25FW (conditional R² 0.79, marginal R² 0.63).

In preliminary longitudinal analysis, when evaluated categorically (worsening defined as: ≥ 20% increase in T25FW and worsening in either video-derived parameter ≥ smallest real difference), the change in these two video-derived parameters agreed with the change in T25FW in 83% of participants.