AI-Based Facial Emotion Analysis in Infants During Complimentary Feeding: A Descriptive Study of Maternal and Infant Influences
Murat Gülşen, Beril Aydın, Güliz Gürer, Sıddika Songül Yalçın

TL;DR
This study uses AI to analyze infants' facial emotions during feeding, finding that maternal and infant traits influence emotional responses more than food type.
Contribution
The novel use of AI-based facial emotion analysis reveals psychosocial influences on infant feeding emotions.
Findings
Infants of mothers with BMI > 30 showed greater surprise during feeding.
Well-educated, non-working mothers had infants displaying more happiness.
Older infants and those introduced to solids before six months showed more anger.
Abstract
Background/Objectives: Infant emotional responses during complementary feeding offer key insights into early developmental processes and feeding behaviors. AI-driven facial emotion analysis presents a novel, objective method to quantify these subtle expressions, potentially informing interventions in early childhood nutrition. We aimed to investigate how maternal and infant traits influence infants’ emotional responses during complementary feeding using an automated facial analysis tool. Methods: This multi-center study involved 117 typically developing infants (6–11 months) and their mothers. Standardized feeding sessions were recorded, and OpenFace software quantified six emotions (surprise, sadness, fear, happiness, anger, disgust). Data were normalized and analyzed via Generalized Estimating Equations to identify associations with maternal BMI, education, work status, and infant…
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Taxonomy
TopicsChild Nutrition and Feeding Issues · Breastfeeding Practices and Influences · Infant Development and Preterm Care
