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NCT Number: NCT07629024

Rehabilitation Assessment of Motor Function In Cerebral Palsy Using Explainable AI

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.

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Key information

Conditions

Cerebral Palsy Children

Age range

4 year–18 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Alfarabi special education center, Islamabad, Pakistan

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About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

AI-Based Functional Mobility and Gait Assessment

Other

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.

Primary outcomes

  1. GMFM-88

    Time frame: 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)

  2. Markerless Gait Analysis

    Time frame: Baseline to 6 months

    Gait videos will be processed using a validated markerless pose estimation framework . 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

  3. Edinburgh visual gait scale (EVGS)

    Time frame: 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%.

  4. WeeFIM (Functional Independence Measure for Children)

    Time frame: 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)

Secondary outcomes

  1. Feasibility of markerless video-based gait analysis for routine physiotherapy assessment in low-resource clinical settings

    Time frame: Through study completion, 12 month

    Feasibility will be evaluated using: (1) video acquisition success rate; (2) data processing completion rate; (3) time required for analysis; and (4) clinician usability and interpretability feedback, obtained through structured questionnaires and semi-structured interviews with practicing physiotherapists regarding SHAP-based model outputs.

  2. Predictive accuracy of the machine learning model for gait and motor function

    Time frame: At model validation ,post data collection ,6 month

    Model performance will be evaluated using RMSE, MAE, and R² for continuous outcomes. Explainability will be assessed using SHAP values, with examination of feature importance consistency across cross-validation folds. based on gait and motor function data collected from participants with ambulatory cerebral palsy.

  3. Robustness of model predictive performance and change in functional and gait outcomes across heterogeneous therapy exposure contexts

    Time frame: Baseline to 6-month follow-up

    The Phase 2 trained model will be applied to 6-month follow-up data without retraining. Predictive performance (RMSE, MAE, R²) will be compared across therapy exposure subgroups (regular vs. irregular/no physiotherapy). Temporal prognosis will additionally be characterized using change from baseline in GMFM-66, WeeFIM, and EVGS, alongside gait symmetry indices derived from video analysis.

Study contacts

Contact information is provided by the study sponsor or research team.

Qamar Mehmood, Phd Rehab

CONTACT

[email protected]

03335151063

Sponsors and collaborators

Lead sponsor

Riphah International University

Other

Registry information

Official study title

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

Important dates

Study start
2026
Primary completion
2027
Study completion
2027
First posted
Jun 5, 2026
Registry last updated
Aug 10, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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