Automated classification of manual exploratory behaviors seen during early childhood using machine learning

This study presents a machine learning approach to automatically classify manual exploratory behaviors in young children. The research demonstrates how computer vision and artificial intelligence can be used to objectively assess motor development patterns, providing tools for researchers and clinicians to better understand early childhood motor behavior.

Recommended citation: Patel, P., Pandya, H., Ranganathan, R., & Lee, M-H. (2024). Automated classification of manual exploratory behaviors seen during early childhood using machine learning. Journal of Motor Learning and Development, 12(2), 386-411.