Multiview child motor development dataset for AI-driven assessment of child development.

ABSTRACT:

Background

Children's motor development is a crucial tool for assessing developmental levels, identifying developmental disorders early, and taking appropriate action. Although the Korean Developmental Screening Test for Infants and Children (K-DST) can accurately assess childhood development, its dependence on parental surveys rather than reliable, professional observation limits it. This study constructed a dataset based on a skeleton of recordings of K-DST behaviors in children aged between 20 and 71 months, with and without developmental disorders. The dataset was validated using a child behavior artificial intelligence (AI) learning model to highlight its possibilities.

Results

The 339 participating children were divided into 3 groups by age. We collected videos of 4 be

SUBMITTER: Kim HH 

PROVIDER: S-EPMC10220505 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature