Remote Video Assessment of Ataxia via SARA^home: Correlation of Pose-Derived Endpoints with Clinician Severity Ratings

Remote assessment of ataxia is increasingly important for patient-centered care and clinical research. SARA^home, a validated video-based adaptation of the Scale for the Assessment and Rating of Ataxia (SARA), enables self-administration of key motor tasks at home.

The aim was to evaluate the correlation of pose-derived gait and stance endpoints from SARA^home videos with clinician-rated severity.

In a multisite observational study, participants recorded SARA^home tasks on consumer mobile devices via the Atom5^TM app. Clinicians rated videos using standardized criteria, blinded to automated outputs. Kinematic measures were extracted via pose estimation and aggregated to video-level features. Videos were aggregated per participant before correlation using Spearman's ρ and Kendall's τ, with 95% cluster-bootstrap confidence intervals.

We analyzed 5418 gait and stance videos from 58 participants across 4 sites (gait n = 2205, stance n = 3213). Score distribution was skewed toward lower severity. For gait, clearance variability (ρ = 0.52 [0.37-0.64]) and median-normalized base of support (ρ = 0.51 [0.35-0.66]) correlated most strongly with item ratings, followed by shoulder sway root mean square (ρ = 0.43 [0.24-0.60]). Adjusted foot clearance (worse limb) correlated negatively (ρ = -0.35 [-0.52 to -0.15]). For stance, anteroposterior sway (ρ = 0.51 [0.36-0.65]), leg alignment variability (ρ = 0.51 [0.36-0.65]), and composite sway (ρ = 0.48 [0.32-0.62]) were most associated with severity. Base of support widened monotonically with severity and was the most reliable gait feature (intraclass correlation coefficient [ICC] = 0.88).

Pose-derived digital endpoints from home-captured SARA^home videos show robust, clinically interpretable correlation with severity, supporting scalable remote phenotyping. Findings motivate longitudinal validation toward clinical and regulatory utility.