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Comprehensive Assessment and Early Prediction of Gross Motor Performance in Toddlers With Graph Convolutional Networks-Based Deep Learning: Development and Validation Study.

Sulim ChunSooyoung JangJin Yong KimChanyoung KoJoo Hyun LeeJaeSeong HongYu-Rang Park
Published in: JMIR formative research (2024)
Using movement videos of toddlers aged 18-35 months, we developed objective and automated models to evaluate each behavior and assess each child's overall gross motor performance. We identified the important behaviors for assessing gross motor performance and developed methods to recognize important moments and body parts while evaluating gross motor performance.
Keyphrases
  • deep learning
  • children with cerebral palsy
  • machine learning
  • convolutional neural network
  • mental health
  • artificial intelligence
  • high throughput
  • neural network