MAMAS

Abstract

Children's problematic eating behavior is one of the biggest problems parents suffer from. Even though the role of parents in building children's eating habit is critical, it is very difficult for parents to continue on the positive interaction with children during mealtime. We describe our preliminary study to develop a system that provides systematic analysis of parent-child mealtime interaction, so as to promote children's healthy eating habits. We propose an application called MAMAS, a mealtime assistant using magnetometer and speech recognition, which 1) noninvasively tracks mealtime interaction patterns, 2) augments analysis with self-reported data and quantification, and 3) provides data-assisted analysis for parents' self-reflection.