AI-based model checks how engaged a child is during rehab and how well they move
Official title: AI-based Model for Rehabilitation Engagement and Motor Performance Evaluation in Pediatric Patients
Run by IRCCS Eugenio Medea · NCT07664033 · Data updated 2026-11-12
A small pilot study tests an artificial intelligence tool that helps therapists see in real time how engaged a child is and how they move during therapy using Lokomat or GRAIL.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 5 Years to 17 Years |
| Sex | All |
| Enrollment | 15 (estimated) |
| Sponsor | IRCCS Eugenio Medea Academic / other |
| Locations | 1 site (Bosisio Parini) |
| Status | Recruiting |
| Started | June 24, 2026 |
| Main results expected | December 31, 2026 |
| Study ends | December 31, 2026 |
| Registry record updated | November 10, 2026 |
| Trial ID | NCT07664033 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Children aged 5–17 with neuromotor impairments who are being treated with Lokomat or GRAIL as part of their standard rehabilitation plan and are able to participate in a single 1-hour session.
✕Probably not a fit
Some participants may not experience a direct benefit from the AI tool if the real-time data are not integrated into therapy or if usability feedback is limited.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This pilot study will enroll 15 pediatric participants aged 5 to 17 with neuromotor impairments, plus at least 5 referring physiotherapists. Each child will undergo a single 1-hour rehabilitation session using Lokomat or GRAIL per their clinical plan, with the AI model providing real-time data on heart rate, engagement, pleasantness, activation, and motor performance to the therapist. After the session, therapists will complete a System Usability Scale questionnaire and offer feedback on the AI tool. The study aims to assess usability and feasibility of the AI-based monitoring model in a pediatric rehabilitation setting. No efficacy endpoints are specified beyond usability and feasibility outcomes.
Why it matters
Potential benefit: If feasible and usable, the AI model could help therapists tailor rehabilitation in real time to a child's engagement and motor responses.
How similar studies have gone: Previous work in rehabilitation technologies has shown potential benefits of real-time monitoring, but this exact AI engagement-monitoring approach in pediatric tech-assisted rehab is exploratory.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Subjects aged between 5 and 17 years with neuromotor impairments who are undergoing rehabilitation therapy using the Lokomat and GRAIL devices, according to the existing clinical plan. Exclusion Criteria: * Uncooperative subjects.
Where it's running
-
Scientific Institute IRCCS E.Medea
Bosisio Parini, Italy Recruiting
Study contacts
- Study coordinator: Fabio Alexander Storm, PhD
- Email: fabio.storm@lanostrafamiglia.it
- Phone: +39 031877111
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.