title: Unobtrusive and Wearable Systems for Automatic Dietary Monitoring.
abstract: The threat of obesity, diabetes, anorexia, and bulimia in our society today has motivated extensive research on dietary monitoring. Standard self-report methods such as 24-h recall and food frequency questionnaires are expensive, burdensome, and unreliable to handle the growing health crisis. Long-term activity monitoring in daily living is a promising approach to provide individuals with quantitative feedback that can encourage healthier habits. Although several studies have attempted automating dietary monitoring using wearable, handheld, smart-object, and environmental systems, it remains an open research problem. This paper aims to provide a comprehensive review of wearable and hand-held approaches from 2004 to 2016. Emphasis is placed on sensor types used, signal analysis and machine learning methods, as well as a benchmark of state-of-the art work in this field. Key issues, challenges, and gaps are highlighted to motivate future work toward development of effective, reliable, and robust dietary monitoring systems.
authors.forename: Temiloluwa
authors.initials: T
authors.lastname: Prioleau
authors.forename: Elliot
authors.initials: E
authors.lastname: Moore Ii
authors.forename: Maysam
authors.initials: M
authors.lastname: Ghovanloo
mesh_terms: D004032:Diet / Q000145:classification*; D015930:Diet Records; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D055617:Micro-Electrical-Mechanical Systems / Q000295:instrumentation*; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods; D015203:Reproducibility of Results; D012648:Self Care / Q000295:instrumentation* / Q000379:methods; D012680:Sensitivity and Specificity