Digital Outcome Assessment Using AI Active Gaming and Motion Capture in Friedreich Ataxia

Overview

Friedreich ataxia (FA) is a rare, inherited condition that progressively affects balance, coordination, and walking. Clinical trials of new FA treatments rely largely on standard clinical rating scales, but these can be tiring for patients, feel disconnected from everyday life, and may not detect small but meaningful changes over time. More objective, sensitive, and patient-relevant ways of measuring movement are needed. This study is developing and testing a new digital way of measuring movement in FA. Participants play short, movement-based computer games on a laptop while a single camera and artificial-intelligence (AI) software track how they move. The proposition is that the way a person plays these games - their speed, accuracy, and movement quality - can provide objective, meaningful measurements of motor function. In the laboratory, these game-based measurements are compared against a "gold-standard" full-body motion-capture system and against established clinical scales to check how accurate and meaningful they are. The study involves both people with Friedreich ataxia (across a range of disease severity) and healthy volunteers. People with FA also take part in a 12-week home phase, playing the games at home each month with remote support, so the researchers can examine whether the digital measurements are reliable when repeated and whether they can detect change over time. The study asks whether these digital, game-based movement measurements are reliable, valid, and sensitive enough to be used as a "fit-for-purpose" digital clinical outcome assessment (dCOA) in future FA clinical trials, and whether patients find the platform acceptable, usable, and relevant to daily life. This is an early-stage feasibility and validation study designed to establish proof of concept rather than to test the effectiveness of a treatment.

Design and rationale STEP-OUT FA is an observational, prospective cohort study (STROBE-compliant) developing and validating a digital clinical outcome assessment (dCOA) for Friedreich ataxia. It addresses a well-documented limitation in FA therapeutic development: existing semi-quantitative clinical outcome assessments are affected by floor and ceiling effects, limited responsiveness across disease stages, and poor patient-perceived relevance, which have contributed to repeated failures of drug trials to meet primary endpoints. The study evaluates whether motor-performance metrics captured during gamified, semi-immersive virtual-reality (VR) tasks, combined with markerless AI motion analysis, can serve as reliable, valid, and responsive outcome measures. Measurement platform The platform is delivered through a standard laptop and integrates three components: (1) FA-adaptable VR gamified tasks (e.g., ball catching, target reaching) with adjustable difficulty; (2) automated extraction of gaming-performance metrics; and (3) a single-camera, patented AI-driven markerless motion-capture system for 3D pose reconstruction (DigiTherapix Ltd), used to derive biomechanical/kinematic metrics. The gaming environment is provided via the MoveHero platform (University of São Paulo). Laboratory validation (healthy controls and FA participants) Validation is conducted at the University of Exeter VSimulator facility against a gold-standard, marker-based full-body motion-capture reference. During a single laboratory visit (\~2 hours), participants complete a familiarisation period followed by a \~20-minute session of four movement-based gaming tasks. Concurrent signals are recorded throughout: full-body optical motion capture (reflective markers on shoulders, elbows, knees, ankles, forehead), continuous heart-rate variability via a Delsys ECG sensor (baseline, task, recovery), and functional near-infrared spectroscopy (fNIRS) over the forehead to index cortical activation. Perceived exertion and fatigue (Borg RPE and Borg VAS Fatigue) are collected after each task, and a short semi-structured interview captures usability and acceptability feedback (audio-recorded for later transcription). FA participants additionally complete clinical characterisation at baseline. Home-based longitudinal phase (FA participants only) To evaluate test-retest reliability and responsiveness, FA participants enter a 12-week home phase with monthly self-administered or remotely supported gaming sessions (\~20-30 minutes) at Weeks 4, 8, and 12, each accompanied by a brief telehealth check-in with a physiotherapist to confirm continued consent, provide support, and monitor adverse events. Data are captured automatically and remotely. A remote follow-up assessment at Week 12 repeats clinical and patient-reported measures and includes a short interview. Analytic approach Concurrent validity is assessed via correlations between digital metrics and established clinical scales; reliability via intraclass correlation coefficients across repeated sessions; and responsiveness via within-subject change and effect sizes, with longitudinal mixed-effects modelling of dCOA trajectories across the home-phase time points. Analyses characterise which individual or composite metrics (gaming-derived versus biomechanical) show optimal measurement properties and best discriminate disease severity. As an exploratory feasibility and validation study establishing proof of concept and psychometric properties, no formal power calculation was performed; the sample size was justified on precision for reliability estimation and on precedent from rare-disease dCOA validation studies. Collaborators and data governance The AI motion-analysis platform is provided by DigiTherapix Ltd (UK) and the gaming platform by the University of São Paulo (Brazil); formal sub-contractor and data-sharing agreements govern intellectual property and data governance. No personally identifiable participant data are transferred outside the UK. Oxford University Hospitals acts as a Participant Identification Centre only.