Wearable Assessment of Upper Limb Recovery After Stroke: From Movement Signals to Meaningful Endpoints

Background: Wearable sensors characterise upper limb movement beyond the clinic, but movement quantity, functional activity, motor restitution, and participation are distinct outcomes. Objective: To appraise the measurement chain connecting wearable signals to meaningful outcomes after stroke and propose a framework for endpoint specification and validation. Methods: Targeted literature retrieval and citation verification were completed on 10 November 2026. Foundational measurement studies, primary accelerometry research, recent digital outcome studies, and methodological guidance were selected purposively. Evidence was organised by construct, reference, setting, responsiveness, and intended use. No pooled estimates or formal certainty grades were produced. Synthesis: Bilateral accelerometry complements clinical capacity tests but cannot alone identify successful grasp, voluntary contribution, or restoration of joint coordination. Laterality ratios can improve when less affected arm activity declines. Classifiers, orientation metrics, finger sensors, and composite measures offer complementary approaches, with limits in activity labels, population coverage, and external validation. A recent digital arm performance scale supports further development; trial-efficiency estimates based on power analysis do not establish patient benefit or endpoint qualification. Measurement error, meaningful change, missingness, and usability require separate evaluation. Conclusion: Credible endpoints require a defined patient-relevant construct, reproducible processing, validation in the intended setting, and a prespecified interpretation of change. Integrating wearable performance measures with impairment, capacity, and movement-strategy assessments supports more precise rehabilitation research and decision-making.