Researchers explored how infants act purposefully by attaching a colorful mobile to their foot and tracking movements with a Vicon 3D motion capture system. The study tested AI's ability to detect changes in infant movement patterns. Findings showed that AI techniques, especially the deep learning model 2D-CapsNet, effectively classified different stages of behavior. Notably, foot movements varied significantly. Looking at how AI classification accuracy changes for each baby gives researchers a new way to understand when and how they start to engage with the world.
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