500 Section - Fit for Medical Robotics: an Italian Initiative to redesign neurorehabilitation through robotics and digital technologies

To present the structure, rationale, and early implementation of Fit for Medical Robotics (Fit4MedRob), an Initiative funded by the Italian Ministry of University and Research (€128.1 million), designed to bridge the translational gap between rehabilitation robotics, clinical practice, and healthcare sustainability. Fit4MedRob aims to generate large-scale, real-world evidence on the effectiveness, efficiency, and organizational impact of robotics and allied digital technologies across neurological and musculoskeletal conditions, addressing unmet rehabilitation needs of patients, caregivers, and healthcare professionals.

Design:

Fit4MedRob is organized into three interconnected Missions. Mission 1 aims to accelerate the clinical translation and large-scale adoption of robotics and digital technologies in rehabilitation through multicenter pragmatic clinical trials, informed by end-user needs collected through dedicated surveys. Study outcomes include clinical scales, neurophysiological, biochemical, and instrumental measures, as well as comprehensive health technology assessment. A common outcome measure, the modified Barthel Index, is included in all trials to enable data pooling. The largest trial plans to enroll 596 post-stroke patients and integrates multidimensional patient profiling (clinical, neuroimaging, neurophysiological, biochemical-genetic, and quantitative instrumental data).

Results:

Mission 1 has launched 26 pragmatic trials with a planned recruitment of approximately 2,000 participants. Enrollment is ongoing, with completion scheduled for November 2026. To date, in the subacute stroke trial, more than 250 patients have been enrolled (mean age: 70.8 years; mean time since acute event: 44.1 days; mean modified Barthel Index score: 44.6).

Conclusion:

Fit4MedRob represents a unique, nation-scale experimental platform for redesigning rehabilitation pathways around patient needs, technological innovation, and healthcare sustainability. It is expected to produce one of the most comprehensive rehabilitation datasets ever assembled, providing robust evidence to inform policymakers, healthcare providers, and regulatory bodies on the clinical, organizational, and economic impact of rehabilitation technologies.