Leveraging technological advances to assess dyadic visual cognition during infancy in high- and low-resource settings

HIGHLIGHTS

• What: The aim of this study was to assess whether headmounted eye trackers could be used to meaningfully examine dyadic infant-caregiver interactions within global, low-resource settings, and generate objective and quantifiable measures. The authors focused on using open-source machine_learning algorithms with the goal of avoiding laborious frame-by-frame hand coding. In Study 1, the authors describe how the authors developed and validated a new pipeline for processing dyadic data from caregivers and infants. This work sets the stage for a larger cross-cultural comparison of dyadic interactions which is presented in Study 2 . . .
  

   

  

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