Related Experiment Video
Updated: Jun 12, 2026
Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
Published on: May 17, 2024
Development, validation and use of artificial-intelligence-related technologies to assess basic motor skills in
Joel Figueroa-Quiñones1, Juan Ipanaque-Neyra2, Heber Gómez Hurtado2,3
1Universidad Autonoma de Ica, Ica, Peru.
Background:
In basic motor skills evaluation, two observers can eventually mark the same child's performance differently. When systematic, this brings serious noise to the assessment. New motion sensing and tracking technologies offer more precise measures of these children's capabilities. We aimed to review current development, validation and use of artificial intelligence-related technologies that assess basic motor skills in children aged 3 to 6 years old.
Methods:
We performed a scoping review in Medline, EBSCO, IEEE and Web of Science databases. PRISMA Extension recommendations for scoping reviews were applied for the full review, whereas the COSMIN criteria for diagnostic instruments helped to evaluate the validation of the artificial intelligence (AI)-related measurements.
Results:
We found 672 studies, from which 12 were finally selected, 7 related to development and validation and 5 related to use. From the 7 technology development studies, we examined their citation networks using Google Scholar and identified 10 subsequent peer-reviewed publications that either enhanced the original technologies or applied them in new research contexts. Studies on AI-related technologies have prioritized development and technological features. The validation of these algorithms was based on engineering standards, focusing on their accuracy and technical performance, but without integrating medical and psychological knowledge about children's motor development. They also did not consider the technical characteristics that are typically assessed in psychometric instruments designed to assess motor skills in children (e.g., the Consensus-based Standards for the Selection of Health Measurement Instruments "COSMIN"). Therefore, the use of these AI-related technologies in scientific research is still limited.
Conclusion:
Clinical measurement standards have not been integrated into the development of AI-related technologies for measuring basic motor skills in children. This compromises the validity, reliability and practical utility of these tools, so future improvement in this type of research is needed.
