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Artificial Intelligence for Infant Motor Screening: Development and Validation

NCT05456126 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 122

Last updated 2025-11-18

No results posted yet for this study

Summary

The purpose of this three-year study is therefore three-fold: (1) Model Development- to apply pose estimation model and tracking recognition model on the movements of a large sample of term and preterm infants under a motor assessment in the laboratory to examine the accuracy of the AI algorithms in identifying individual movements using physical therapists' results as gold standards; (2) Model Validation- to examine the performance of the AI algorithms on the same term and preterm infants' movements when video recorded by the parents at home between the laboratory assessment ages using physical therapists' results as gold standards; and (3) Concurrent and Predictive Validity of AI Movement Sets- to select the identifiable movement classes into AI movement sets for individual ages to examine their concurrent validity with physical therapists' results and predictive validity on developmental outcomes at 18 months of age in these infants.

Conditions

  • Motor Disorders

Sponsors & Collaborators

  • National Health Research Institutes, Taiwan

    collaborator OTHER

  • National Taiwan University Hospital

    lead OTHER

Principal Investigators

  • Suh-Fang Jeng, Professor · School and Graduate Institute of Physical Therapy, National Taiwan University

Eligibility

Min Age
4 Months
Max Age
18 Months
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2021-08-01
Primary Completion
2025-05-17
Completion
2025-05-17

Countries

  • Taiwan

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05456126 on ClinicalTrials.gov