Detection and characterization of food intake by wearable sensors

Food intake provides energy and nutrients to sustain human life. Studying the ingestive behavior of individuals is of particular interest for understanding and treatment of medical conditions strongly associated with food intake, such as obesity and eating disorders. Traditionally, ingestive behavior in humans has been assessed through self-monitoring of food intake. However, this approach is inaccurate, time consuming, and suffers from the observation and misreporting effects. Wearable sensors present a compelling alternative to overcome limitations of self-reporting methods. These sensors can potentially provide more objective measurements of food intake by monitoring physiological processes related to one or more stages of the food consumption process: hand-to-mouth gestures, bites, chewing, or swallowing. Specialized signal processing and pattern recognition methodologies use the sensor data to automatically detect and characterize each intake episode. Particularly, timing and duration of the meals, the mass and volume of ingestion, caloric and nutritional content of a meal, and the rate of ingestion could potentially be estimated from sensor data. This chapter presents an overview of the wearable sensors and accompanying methodologies that have been proposed for monitoring ingestive behavior in humans.

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