AI-based Model for Rehabilitation Engagement and Motor Performance Evaluation in Pediatric Patients

NCT ID: NCT06993389

Last Updated: 2025-07-09

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ACTIVE_NOT_RECRUITING

Total Enrollment

40 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-06-09

Study Completion Date

2025-11-30

Brief Summary

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What is the purpose of this study? This study wants to learn how the physiological signals and movement data can help researchers understand and predict how children with neuromotor impairments engage with rehabilitation.

Who can take part? 40 participants between 5 and 17 years old will take part. Half of them will be children with neurotypical development (control). The other half will be children with neuromotor impairments.

What will happen in the study? Children within the control group will take part in 1 rehabilitation session, while those with neuromotor impairments will take part in 2 to 3 rehabilitation sessions as part of the treatment plan already provided by their referring physicians.

During each session, researchers will collect: (i) physiological signals like heart activity (ECG), heart rate variability (HRV), and electrodermal activity (EDA); (ii) movement data; (iii) exergames scores and motor performance data; (iv) questionnaires filled out by therapists to understand how engaged the participant is.

Children will use one of two technology-assisted rehabilitation systems during their sessions: either the Lokomat (robotic exoskeleton that supports children with impairments in walking) or the GRAIL system (a treadmill system with motion tracking and extended reality).

Why is this study important? Researchers will use the data to understand and predict how each child responds to therapy and engage with it. These analyses will help therapists adjust rehabilitation settings in real-time, offering more personalized and effective care for children with neuromotor impairments.

Detailed Description

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Conditions

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Neuromotor Impairments

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Neuromotor impaired

Inapplicable

Intervention Type OTHER

Inapplicable

Control

Inapplicable

Intervention Type OTHER

Inapplicable

Interventions

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Inapplicable

Inapplicable

Intervention Type OTHER

Eligibility Criteria

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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.
Minimum Eligible Age

5 Years

Maximum Eligible Age

17 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Politecnico di Milano

OTHER

Sponsor Role collaborator

IRCCS Eugenio Medea

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Scientific Institute IRCCS E.Medea

Bosisio Parini, LC, Italy

Site Status

Countries

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Italy

References

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Costantini S, Falivene A, Chiappini M, Malerba G, Dei C, Bellazzecca S, Storm FA, Andreoni G, Ambrosini E, Biffi E. Artificial intelligence tools for engagement prediction in neuromotor disorder patients during rehabilitation. J Neuroeng Rehabil. 2024 Dec 19;21(1):215. doi: 10.1186/s12984-024-01519-2.

Reference Type BACKGROUND
PMID: 39702317 (View on PubMed)

Koenig A, Omlin X, Zimmerli L, Sapa M, Krewer C, Bolliger M, Muller F, Riener R. Psychological state estimation from physiological recordings during robot-assisted gait rehabilitation. J Rehabil Res Dev. 2011;48(4):367-85. doi: 10.1682/jrrd.2010.03.0044.

Reference Type BACKGROUND
PMID: 21674389 (View on PubMed)

Graffigna G, Barello S, Riva G, Castelnuovo G, Corbo M, Coppola L, Daverio G, Fauci A, Iannone P, Ricciardi W, Bosio AC; CCIPE Working Group. [Recommandation for patient engagement promotion in care and cure for chronic conditions.]. Recenti Prog Med. 2017 Nov;108(11):455-475. doi: 10.1701/2812.28441. Italian.

Reference Type BACKGROUND
PMID: 29149163 (View on PubMed)

Flynn R, Walton S, Scott SD. Engaging children and families in pediatric Health Research: a scoping review. Res Involv Engagem. 2019 Nov 4;5:32. doi: 10.1186/s40900-019-0168-9. eCollection 2019.

Reference Type BACKGROUND
PMID: 31700676 (View on PubMed)

Bray L, Appleton V, Sharpe A. The information needs of children having clinical procedures in hospital: Will it hurt? Will I feel scared? What can I do to stay calm? Child Care Health Dev. 2019 Sep;45(5):737-743. doi: 10.1111/cch.12692. Epub 2019 Jul 18.

Reference Type BACKGROUND
PMID: 31163093 (View on PubMed)

Other Identifiers

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RC 2024-2026 to E. Biffi

Identifier Type: OTHER_GRANT

Identifier Source: secondary_id

L2-246

Identifier Type: -

Identifier Source: org_study_id

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