The convergence of artificial intelligence (AI) and robotic medical devices marks a new chapter for stroke rehabilitation. A multicenter clinical trial, titled “Clinical Validation of an AI-Based Decision Support System for Robotic Upper Limb Rehabilitation in Patients with Stroke (CO-AIDER),” delves into the efficacy of AI-integrated robotic therapies for upper limb rehabilitation in post-stroke patients. This initiative, sponsored by Fondazione Don Carlo Gnocchi Onlus, Fondazione Policlinico Universitario Campus Bio-Medico, and Scuola Superiore Sant’Anna di Pisa, is slated to begin recruitment.
In this article
- What changed?
- What are the trial’s objectives?
- How will the study be conducted?
- FAQs
- Conclusion
- Disclaimer
- Full announcement
What changed?
On October 1, 2025, it was confirmed that the CO-AIDER study would commence soon, as noted in the ClinicalTrials.gov registry. This trial is not yet recruiting as of now but represents a significant effort to explore AI’s role in post-stroke rehabilitation.
The trial will monitor the clinical impact of an AI-based decision support system, designed for integration with robotic upper limb rehabilitation devices. Unlike conventional robotic therapies, this advanced approach aims to personalize and optimize treatment paths to enhance patient outcomes.
What are the trial’s objectives?
The primary aim of this research is to assess the therapeutic efficacy and added value of AI in robotic upper limb rehabilitation. Secondary goals include validating the safety of the AI-supported devices and comparing them with traditional robotic rehabilitation systems.
Key conditions targeted in this trial include post-stroke recovery, specifically among ischemic and hemorrhagic stroke patients. The interventions under evaluation are:
- Robotic upper limb rehabilitation with AI support
- Robotic upper limb rehabilitation without AI support
The trial will collect and analyze clinical data to substantiate the safety and performance profile of the device as per regulatory standards.
How will the study be conducted?
Two patient groups will undergo robotic therapy sessions. One group will benefit from AI-enhanced robotic support, which intelligently adjusts therapy based on real-time data. The control group will use robotic rehabilitation devices without the AI feature to serve as a benchmark.
The study will evaluate functional recovery, patient adherence, and the decision support system’s accuracy. Measurable outcomes will follow established rehabilitation efficacy metrics, with patient safety and device usability being closely monitored.
This trial is co-managed by renowned healthcare and research entities in Italy, ensuring academic rigor and compliance with medical device regulations.
FAQs
- What is the purpose of the trial?
The trial aims to validate the effectiveness and safety of AI-based decision support systems in robotic rehabilitation for stroke patients. - Who are the sponsors?
The study is sponsored by Fondazione Don Carlo Gnocchi Onlus, Fondazione Policlinico Universitario Campus Bio-Medico, and Scuola Superiore Sant’Anna di Pisa. - When will recruitment start?
As of now, the trial is not yet recruiting. A timeline for recruitment will likely be announced soon. - What conditions are targeted?
The trial will focus on stroke, ischemic stroke, hemorrhagic stroke, and upper limb rehabilitation.
Conclusion
The CO-AIDER study exemplifies how AI innovation continues to advance medical device technology, particularly in robotic rehabilitation. While clinical validation is pending, the trial represents a critical step toward ensuring innovative therapies align with safety and efficacy standards. Stakeholders in clinical, quality, and regulatory teams should monitor its progress.
Disclaimer
This article is for informational purposes only and is not intended as legal or regulatory advice. Consult professional resources for decisions related to clinical trials or compliance.
Full announcement
For full information about the announcement, see the link below.
https://clinicaltrials.gov/study/NCT07199322?term=medical+device