AI‐Based Exergaming as a Digital Assessment Tool for Post‐Stroke Upper‐Limb Function: Protocol for a Feasibility Study

ABSTRACT Background and Purpose Accurate assessment of upper limb motor function is critical for guiding effective rehabilitation strategies in stroke survivors. The Fugl‐Meyer Assessment for Upper Extremity (FMA‐UE) is a widely used clinical tool, yet it is time‐consuming and subject to inter‐patient variability. A low‐cost, computer vision‐based exergame was developed to provide a remote rehabilitation alternative that also enables motor assessment. This approach represents a promising alternative for scalable and objective assessment, but requires validation. This study aims to evaluate the feasibility and preliminary validity of a computer vision‐based exergame system for assessing upper limb motor function in individual post‐stroke. Specifically, it investigates correlations between kinematic features derived from gameplay and FMA‐UE scores. It is expected that gameplay‐derived metrics, such as range of motion, jitter index, and average hand angle, will show moderate to strong correlations with the FMA‐UE, supporting the exergame's potential as a remote assessment tool. Methods This is a cross‐sectional feasibility and preliminary concurrent validity pilot study with 15–30 individuals with chronic stroke. Participants will perform a markerless camera‐based exergame producing pseudo‐3D hand coordinates using MediaPipe‐based hand tracking. Kinematic features, including range of motion, average hand angle, and jitter index, will be extracted from gameplay. Each participant will also be evaluated using the FMA‐UE by a certified therapist. Correlation and regression analyses will assess the relationship between exergame metrics and clinical scores. Usability will be assessed using the System Usability Scale (SUS). Results We expect moderate to strong correlations between selected gameplay metrics and FMA‐UE scores, particularly for range of motion, average hand angle, total traveled distance, jitter index, and score. The system is also expected to demonstrate high usability, indicating its feasibility for broader use in rehabilitation settings. Discussion If validated, the proposed exergame may serve as an accessible and scalable digital tool to support future development of objective assessment tools in stroke rehabilitation, potentially reducing clinical workload and enabling remote evaluations. A future large‐scale study will evaluate test–retest reliability, longitudinal responsiveness, and home‐based implementation.