PHRASE delivered a complete, GDPR-aligned pipeline that links data capture, analysis, and personalised stroke rehabilitation. The core infrastructure is a hospital-operated virtual research environment, integrated with a secure research cloud and a knowledge graph, so sensitive data are processed in isolated, auditable workspaces while non-sensitive metadata remain findable. This backbone supported all clinical data flows.
Patient and clinician apps were upgraded with clearer onboarding, short in-app tutorials, a virtual coach with reminders, and structured at-home assessments of motor and cognitive function. Wearable-based arm-use monitoring and an adaptive difficulty engine were hardened through cross-device testing to improve reliability.
AI components moved from prototypes to evaluated modules embedded in the pipeline. A “digital diagnosis” estimates standard clinical scales from day-to-day interaction data and reports confidence; a prognosis model predicts recovery trajectories on widely used stroke scales; and training is personalised automatically. Internal evaluations on harmonised datasets showed strong agreement with clinical measures and accurate class predictions, and outputs are generated server-side and shown in clinician dashboards for remote review.
Clinical work progressed from feasibility to a randomised controlled trial. The feasibility study enrolled 88 participants across five centres and reported good usability (System Usability Scale 70.21). The trial was registered and approved, sites were activated, electronic case-report forms configured, and enrolment began; confirmatory effectiveness and agreement analyses will follow completion as planned.
In sum, PHRASE delivered a secure analytics backbone, a hardened telerehabilitation suite, uncertainty-aware diagnosis and prognosis integrated into clinician tools, and feasibility evidence with a live pathway to confirmatory trial outcomes.
