The Automated Vestibular Rehabilitation System: Normative Data From a Machine Vision‐Guided Platform

ABSTRACT Objective(s) Vestibular rehabilitation therapy (VRT) is an efficient treatment for dizziness and vertigo, but its accessibility remains limited. This study evaluates the feasibility and performance of a machine vision‐based automated alternative—the Automated Vestibular Rehabilitation System (AVRS)—as a more accessible approach to delivering VRT. Methods Forty age‐ and sex‐matched adults without balance disorders or recent head injury completed one standard VRT exercise, X1, in seated and standing positions using the AVRS, which tracked real‐time head and eye movements. Gain, the ratio of eye to head velocity near the neutral head position, was calculated using median values and interquartile ranges. Test‐retest reliability (TRTR) was assessed in a subset of 20 participants using intraclass correlation coefficients (ICCs) with 95% confidence intervals. Results All participants successfully completed the AVRS‐guided vestibular exercises. The n = 20 person test‐retest reliability subset returned after 27 ± 9 days. Mean VOR gain approximated the expected physiologic norms (~−1.0) across sessions irrespective of frequency (Session 1: −0.98 ± 0.04; Session 2: −0.99 ± 0.03). Overall reliability between sessions was moderate (ICC (3, 1): 0.59 [95% CI: 0.37–0.75], p < 0.001). Conclusion The AVRS demonstrated moderate reliability and accurate VOR gain measurement in healthy adults, supporting its potential as a scalable, accessible tool for VRT delivery, with normative data to guide therapeutic progression in clinical populations. Level of Evidence 4.