DietGlance: Dietary Monitoring and Personalized Analysis at a Glance with Knowledge-Empowered AI Assistant
Journal:
arXiv
Published Date:
Feb 3, 2025
Abstract
Growing awareness of wellness has prompted people to consider whether their
dietary patterns align with their health and fitness goals. In response,
researchers have introduced various wearable dietary monitoring systems and
dietary assessment approaches. However, these solutions are either limited to
identifying foods with simple ingredients or insufficient in providing analysis
of individual dietary behaviors with domain-specific knowledge. In this paper,
we present DietGlance, a system that automatically monitors dietary in daily
routines and delivers personalized analysis from knowledge sources. DietGlance
first detects ingestive episodes from multimodal inputs using eyeglasses,
capturing privacy-preserving meal images of various dishes being consumed.
Based on the inferred food items and consumed quantities from these images,
DietGlance further provides nutritional analysis and personalized dietary
suggestions, empowered by the retrieval augmentation generation module on a
reliable nutrition library. A short-term user study (N=33) and a four-week
longitudinal study (N=16) demonstrate the usability and effectiveness of
DietGlance, offering insights and implications for future AI-assisted dietary
monitoring and personalized healthcare intervention systems using eyewear.
