Abstract
Background/Objectives: Dietary microstructure affects energy intake. Traditional Universal Eating Monitors (UEMs) offer accuracy but are limited for monitoring diverse diets. We developed the 'Feeding Table', a novel UEM that simultaneously tracks intake of up to 12 foods, enabling high-resolution monitoring of eating microstructure for multiple foods simultaneously. Methods: Forty-nine healthy volunteers participated: 15 (10 male, 8 female) in a location preference experiment and 31 (15 male, 16 female) in a standard meal test. The location preference study involved four weekly sessions. Participants received a standardized breakfast based on individual energy needs; lunch intake was measured 3 h later with food items in pseudo-randomized positions. The standard meal test occurred over two consecutive days to assess the Feeding Table's performance in monitoring eating behavior under standardized conditions. Results: In two consecutive days of standard meal tests, the Feeding Table showed reasonable day-to-day repeatability for energy and macronutrient intake (energy: r = 0.82; fat: r = 0.86; carbohydrate: r = 0.86; protein: r = 0.58). Among the four repeated intake measurements, the results demonstrated high intra-class correlation coefficients (ICCs: energy 0.94, protein 0.90, fat 0.90, and carbohydrate 0.93). No significant positional bias was observed (energy: p = 0.07; macronutrients: p = 0.70). Conclusions: The Feeding Table maintains UEM accuracy while enabling multi-food, real-time monitoring of dietary microstructure and food choice, offering enhanced precision for studying eating behaviors.