Questa pagina è stata tradotta automaticamente e l'accuratezza della traduzione non è garantita. Si prega di fare riferimento al Versione inglese per un testo di partenza.

Rehabilitation Assessment of Motor Function In Cerebral Palsy Using Explainable AI

1 giugno 2026 aggiornato da: Riphah International University

Rehabilitation Assessment of Motor Function in Ambulatory Children With Cerebral Palsy Using Explainable Machine Learning

The goal of this observational study is to develop and validate an AI-based prediction model for functional mobility and gait outcomes in children with cerebral palsy using low-cost clinical and gait data collected in rehabilitation settings in Pakistan. The study aims to determine whether machine learning models can accurately predict mobility status, gait symmetry, and functional independence in ambulatory and non-ambulatory children with cerebral palsy.

The main questions it aims to answer are:

  • Can clinical and gait-related variables accurately predict functional mobility and gait outcomes in children with spastic cerebral palsy?
  • Can video-based assessment tools provide clinically useful data for AI-based rehabilitation assessment in low-resource settings?

Researchers will analyze clinical, functional, and gait data to identify patterns associated with mobility limitations and rehabilitation outcomes.

Participants will:

  • Undergo clinical and functional assessments, including measures of balance, mobility, posture, and functional independence.
  • Perform gait and movement tasks while data are collected using AI-based video analysis tools.
  • Participate in routine rehabilitation sessions while their movement and functional performance are recorded for analysis.
  • Provide demographic and clinical information relevant to cerebral palsy severity and functional status.

Panoramica dello studio

Stato

Non ancora reclutamento

Condizioni

Intervento / Trattamento

Descrizione dettagliata

Children with cerebral palsy (CP) commonly experience limitations in functional independence and mobility, which significantly affect participation and quality of life. Accurate assessment of these functional abilities is essential for rehabilitation planning, prognosis estimation, and monitoring treatment outcomes. However, conventional assessment methods largely depend on therapist observation and standardized clinical scales, which may be subjective, time-consuming, and less sensitive to complex interactions among clinical variables. In low-resource rehabilitation settings, the limited availability of advanced assessment technologies further restricts objective and data-driven clinical decision-making. Therefore, there is a growing need for innovative, accessible, and reliable approaches to improve rehabilitation assessment in children with CP.

The novelty of this study lies in the application of machine learning techniques to rehabilitation assessment of functional independence and mobility in children with cerebral palsy. Unlike traditional approaches that rely solely on isolated clinical interpretation, this study aims to integrate multiple clinical and functional parameters to identify predictive patterns associated with mobility and independence outcomes. The proposed approach introduces a data-driven and potentially more objective framework for rehabilitation assessment, supporting early identification of functional limitations and personalized intervention planning. Additionally, conducting this research in a low-resource context contributes further novelty by exploring the feasibility of implementing machine learning-based rehabilitation assessment tools in settings where advanced gait laboratories and expensive technologies are not readily available.

Tipo di studio

Osservativo

Iscrizione (Stimato)

200

Contatti e Sedi

Questa sezione fornisce i recapiti di coloro che conducono lo studio e informazioni su dove viene condotto lo studio.

Contatto studio

Luoghi di studio

  • Pakistan
      • Islamabad, Pakistan
      • Islamabad, Pakistan
        • Army special education Academy
      • Islamabad, Pakistan
      • Karachi, Pakistan
        • Karachi institue of neurological diseases and rehabilitation(KIND-R)
        • Contatto:
        • Investigatore principale:
          • Sidra Ghias, PhD*
        • Contatto:

Criteri di partecipazione

I ricercatori cercano persone che corrispondano a una certa descrizione, chiamata criteri di ammissibilità. Alcuni esempi di questi criteri sono le condizioni generali di salute di una persona o trattamenti precedenti.

Criteri di ammissibilità

Età idonea allo studio

  • Bambino
  • Adulto

Accetta volontari sani

No

Metodo di campionamento

Campione non probabilistico

Popolazione di studio

Children with cerebral palsy classified within Gross Motor Function Classification System (GMFCS) Levels I-III who are ambulatory with or without assistive devices and receiving routine physiotherapy rehabilitation. Participants from all cerebral palsy subtypes will be included for clinical, functional, and gait assessment related to AI-based evaluation of functional mobility and gait outcomes.

Descrizione

Inclusion Criteria:

  • Age 4 to18 years
  • Diagnosed any motor type of cerebral palsy (spastic, dyskinetic, ataxic, mixed),)
  • GMFCS levels I -III (able to walk with or without an assistive device).
  • All participants must be able to ambulate at least 10 meters with or without an assistive device.
  • Capable of following simple verbal instructions.
  • Parental informed consent and child assent

Exclusion Criteria:

  • Recent orthopedic or neurosurgical interventions (<6 months).
  • Uncontrolled seizures affecting gait.
  • Non-ambulatory (GMFCS IV-V) or cognitive impairments preventing cooperation.

Piano di studio

Questa sezione fornisce i dettagli del piano di studio, compreso il modo in cui lo studio è progettato e ciò che lo studio sta misurando.

Come è strutturato lo studio?

Dettagli di progettazione

Coorti e interventi

Gruppo / Coorte
Intervento / Trattamento
Ambulatory Children with Spastic Cerebral Palsy (GMFCS I-III)
Children diagnosed with spastic cerebral palsy who are ambulatory and classified within Gross Motor Function Classification System (GMFCS) Levels I to III. Participants will undergo clinical, functional, and gait assessments for AI-based prediction of functional mobility and gait outcomes
Altro: AI-Based Functional Mobility and Gait Assessment
Participants will continue receiving their standard/routine physiotherapy rehabilitation program as prescribed by their treating therapist. The study will involve observational collection of clinical, functional, and gait-related data using standardized assessment tools, and AI-based video analysis. No additional therapeutic intervention will be administered specifically for research purposes.

Cosa sta misurando lo studio?

Misure di risultato primarie

Misura del risultato
Misura Descrizione
Lasso di tempo
GMFM-66
Lasso di tempo: Baseline to 6 months followup
GMFM (Gross Motor Function Measure) Reliability: Excellent. Internal consistency Cronbach's α ~0.997-1.00; intra- and inter-rater ICC ~0.994-0.999 (both GMFM-88 & GMFM-66) Validity: Construct and concurrent validity supported by strong correlations with related motor function classifications (e.g., GMFCS, PEDI mobility)
Baseline to 6 months followup
Markerless Gait Analysis
Lasso di tempo: Baseline to 6 months

Gait videos will be processed using a validated markerless pose estimation framework (MediaPipe) Spatiotemporal and kinematic gait parameters will be extracted, including but not limited to:

  • Step length symmetry
  • Cadence
  • Stride time variability
  • Joint angle trajectories
  • Temporal asymmetry indices
Baseline to 6 months
Edinburgh visual gait scale (EVGS)
Lasso di tempo: Baseline to 6 Months
Edinburgh visual gait scale (EVGS) EVGS can be a supportive tool that adds quantitative data instead of only qualitative assessment to a video only gait evaluation. Interobserver agreement is 60-90% and Kappa values are 0.18-0.85 for the 17 items in EVGS. Reliability is higher for distal segments (foot/ankle/knee 63-90%; trunk/pelvis/hip 60-76%). Agreement between EVGS and 3DGA is 52-73%.
Baseline to 6 Months
WeeFIM (Functional Independence Measure for Children)
Lasso di tempo: Baseline to 6 months
WeeFIM (Functional Independence Measure for Children) Reliability: High internal consistency and ICCs (motor and cognitive scales) ~0.91-0.98 in children with cerebral palsy Validity: Construct and external validity supported (scale fits Rasch model expectations and correlates with related developmental measures)
Baseline to 6 months

Misure di risultato secondarie

Misura del risultato
Misura Descrizione
Lasso di tempo
System usabiity scale (SUS)
Lasso di tempo: 6 months
10 items likert scale questionnaire evaluating percieved usability and acceptability
6 months

Collaboratori e investigatori

Qui è dove troverai le persone e le organizzazioni coinvolte in questo studio.

Sponsor

Riphah International University

Investigatori

  • Investigatore principale: Sidra Ghias, PhD* Rehab, Riphah International university Isalambad

Studiare le date dei record

Queste date tengono traccia dell'avanzamento della registrazione dello studio e dell'invio dei risultati di sintesi a ClinicalTrials.gov. I record degli studi e i risultati riportati vengono esaminati dalla National Library of Medicine (NLM) per assicurarsi che soddisfino specifici standard di controllo della qualità prima di essere pubblicati sul sito Web pubblico.

Studia le date principali

Inizio studio (Stimato)

10 giugno 2026

Completamento primario (Stimato)

30 giugno 2027

Completamento dello studio (Stimato)

30 dicembre 2027

Date di iscrizione allo studio

Primo inviato

18 maggio 2026

Primo inviato che soddisfa i criteri di controllo qualità

1 giugno 2026

Primo Inserito (Effettivo)

5 giugno 2026

Aggiornamenti dei record di studio

Ultimo aggiornamento pubblicato (Effettivo)

5 giugno 2026

Ultimo aggiornamento inviato che soddisfa i criteri QC

1 giugno 2026

Ultimo verificato

1 giugno 2026

Maggiori informazioni

Termini relativi a questo studio

Parole chiave

Altri numeri di identificazione dello studio

  • RCRAHS-ISB/REC/PhD/011111

Piano per i dati dei singoli partecipanti (IPD)

Hai intenzione di condividere i dati dei singoli partecipanti (IPD)?

NO

Informazioni su farmaci e dispositivi, documenti di studio

Studia un prodotto farmaceutico regolamentato dalla FDA degli Stati Uniti

No

Studia un dispositivo regolamentato dalla FDA degli Stati Uniti

No

Queste informazioni sono state recuperate direttamente dal sito web clinicaltrials.gov senza alcuna modifica. In caso di richieste di modifica, rimozione o aggiornamento dei dettagli dello studio, contattare register@clinicaltrials.gov. Non appena verrà implementata una modifica su clinicaltrials.gov, questa verrà aggiornata automaticamente anche sul nostro sito web .

Prove cliniche su AI-Based Functional Mobility and Gait Assessment

Cerca prove simili

Sponsor e collaboratori

Condizioni mediche

Interventi farmacologici

CROs by country

CROs in Brazil

Condizioni

Malattie rare

Interventi farmacologici

Supplementi dietetici

Sponsor / Collaboratori

Sedi

Sottoscrivi