DETECTION OF SCREEN USAGE DURING EATING EVENTS AMONG PRESCHOOL-AGED CHILDREN

Detection of screen use during eating events in young children is a challenging task, as preschool-aged children have limited ability to self-report. The relationship between screen use and dietary intake is not yet well understood. In this study, we utilized a wearable camera to capture egocentric images and identify screen usage during eating events. The study involved 25 children (ages 3–5) who wore the device for two full days. The Recognize Anything Model (RAM) was used to analyze the images, generating object tags along with their associated tag scores. Using ANOVA F-values, the top 20 image tags were selected, and their confidence scores were employed as features in a Random Forest classifier to distinguish food and beverage images from non-food images. Screen use was estimated using the YOLO-5 object detection model. Our proposed framework achieved an accuracy of 87.7% for eating event detection, 95.7% for detecting eating events involving screen use, 66.1% for food and beverage image detection, and 83.5% for detecting screen use with food and beverage images. These findings underscore the potential of wearable cameras for monitoring screen time during eating events in preschool-aged children.