Using AI to track rehabilitation engagement and motor performance in children with neuromotor impairments
AI-based Model for Rehabilitation Engagement and Motor Performance Evaluation in Pediatric Patients
IRCCS Eugenio Medea · NCT06993389
This project will test an AI-based system that uses heart and skin signals plus movement data to see if it can track engagement and motor performance in children aged 5 to 17 with and without neuromotor impairments.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 40 (estimated) |
| Ages | 5 Years to 17 Years |
| Sex | All |
| Sponsor | IRCCS Eugenio Medea (other) |
| Locations | 1 site (Bosisio Parini, LC) |
| Trial ID | NCT06993389 on ClinicalTrials.gov |
What this trial studies
Researchers will enroll 40 children aged 5–17, with half having neuromotor impairments undergoing rehabilitation and half being neurotypical controls. Control participants will attend one rehabilitation session, while participants with neuromotor impairments will contribute two to three sessions that align with their existing clinical care using Lokomat and GRAIL devices. During each session the team will collect physiological signals (ECG, HRV, EDA), movement and gait data, exergame performance scores, and therapist questionnaires. Machine learning models will be developed to link these signals to engagement and motor performance to explore predictive markers of therapy engagement and response.
Who should consider this trial
Good fit: Children aged 5–17 who are either neurotypical or have neuromotor impairments and are receiving rehabilitation with Lokomat and GRAIL devices, and who can cooperate with study procedures, are ideal candidates.
Not a fit: Children who are uncooperative, outside the 5–17 age range, or not undergoing rehabilitation with the specified Lokomat/GRAIL equipment may not be able to participate or benefit from the findings.
Why it matters
Potential benefit: If successful, the approach could help therapists personalize rehabilitation by identifying when a child is engaged or likely to respond, potentially improving therapy effectiveness.
How similar studies have performed: Related research using physiological and movement data with machine learning has shown promise in adults and controlled settings, but real-world pediatric applications in rehabilitation remain relatively novel.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Subjects aged between 5 and 17 with typical development. * 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 this trial is running
Bosisio Parini, LC
- Scientific Institute IRCCS E.Medea — Bosisio Parini, LC, Italy (RECRUITING)
Study contacts
- Study coordinator: Fabio A Storm, PhD
- Email: fabio.storm@lanostrafamiglia.it
- Phone: +39 031877111
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions: Neuromotor Impairments, Engagement, Motor rehabilitation, Neuromotor impairments, Gait, Psychophysiology