Intake Monitoring

Intake monitoring, aiming to objectively measure food and beverage consumption, is a rapidly evolving field driven by the need for accurate dietary assessment in diverse settings. Current research focuses on developing automated systems using computer vision (including convolutional neural networks and autoencoders), sensor data (e.g., radar, impedance sensing), and large language models (LLMs) to analyze images, videos, and other data streams. These advancements offer significant potential for improving dietary tracking in healthcare (e.g., for elderly care and malnutrition prevention), nutrition research, and personalized health interventions, moving beyond the limitations of self-reporting methods.