Abstract
Modernizing dietary surveillance is essential for addressing diet-related chronic disease, yet traditional self-report tools remain burdensome and error-prone. Edna, a mobile ecological momentary diet assessment (mEMDA) platform, was developed through a multidisciplinary, user-centered process to enable real-time, low-burden dietary reporting with image-assisted portion estimation and automated nutrient coding. In three iterative rounds of national remote testing (N = 146 U.S. adults, 19-65 years), participants were randomized to event- or interval-contingent sampling for 14 days. System Usability Scale (SUS) scores rose from 71.7 to 78.8, surpassing the average benchmark for digital health apps (SUS = 68). Engagement ranged from 92.5-97.6% of study days between rounds, and compliance among interval-contingent users varied between rounds (76-87%). Participants rated portion-size images and navigation as intuitive and culturally inclusive. Edna achieved above-average usability and strong engagement, demonstrating the feasibility of scalable, EMA-based dietary surveillance for digital public-health nutrition monitoring.