About this Research Topic
Modern technology and quantitative methods of mathematical modeling present an unprecedented opportunity for development of objective methods for monitoring and modification of diet and ingestive behavior. Accurate and objective measurement of dietary intake, including energy and nutritional content of ingested food and eating microstructure, represent arguably the most difficult and still unresolved problem in studying human nutrition.
In the recent years, wearable sensors have been widely explored as a means for detection of food intake and characterization of eating episodes in terms of hand-to-mouth gestures, chews and swallows. At the same time, image-based methods are emerging for nutritional analysis of actively or passively captured food imagery. These methods may be supplemented by techniques of natural language processing for extraction of food descriptions from speech. The objective sensor-derived metrics provide a rich ground for mathematical modeling of ingestions patterns and, potentially, energy balance. Last but not the least, modern technology allows to provide tailored just-in-time adaptive interventions on eating behaviors by using sensors and mobile devices.
This Research Topic focuses on emerging techniques of dietary and behavioral assessment relying on wearable sensors as the primary source of the information; quantitative techniques for modeling of human ingestive behavior, energy intake, energy expenditure and energy balance; methods of image and video recognition for food analysis; and other related methods and devices.
Keywords: Nutrition, food intake, energy intake, wearable sensors, image recognition
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