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Feeding Behavior

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Assessment of In-Meal Eating Behaviour using Fuzzy SVM.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Certain patterns of eating behaviour during meal have been identified as risk factors for long-term abnormal eating development in healthy individuals and, eventually, can affect the body weight. To detect early signs of problematic eating behaviour,...

Detecting Meals In the Wild Using the Inertial Data of a Typical Smartwatch.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automated and objective monitoring of eating behavior has received the attention of both the research community and the industry over the past few years. In this paper we present a method for automatically detecting meals in free living conditions, u...

Prediction of the Influential Factors on Eating Behaviors: A Hybrid Model of Structural Equation Modelling-Artificial Neural Networks.

TheScientificWorldJournal
The importance of eating behavior risk factors in the primary prevention of obesity has been established. Researchers mostly use the linear model to determine associations among these risk factors. However, in reality, the presence of nonlinearity am...

Validation of a Deep Learning System for the Full Automation of Bite and Meal Duration Analysis of Experimental Meal Videos.

Nutrients
Eating behavior can have an important effect on, and be correlated with, obesity and eating disorders. Eating behavior is usually estimated through self-reporting measures, despite their limitations in reliability, based on ease of collection and ana...

Food Liking-Based Diet Quality Indexes (DQI) Generated by Conceptual and Machine Learning Explained Variability in Cardiometabolic Risk Factors in Young Adults.

Nutrients
The overall pattern of a diet (diet quality) is recognized as more important to health and chronic disease risk than single foods or food groups. Indexes of diet quality can be derived theoretically from evidence-based recommendations, empirically fr...

Exploring Abnormal Behavior Patterns of Online Users With Emotional Eating Behavior: Topic Modeling Study.

Journal of medical Internet research
BACKGROUND: Emotional eating (EE) is one of the most significant symptoms of various eating disorders. It has been difficult to collect a large amount of behavioral data on EE; therefore, only partial studies of this symptom have been conducted. To p...

The acoustic near-field measurement of aye-ayes' biological auditory system utilizing a biomimetic robotic tap-scanning.

Bioinspiration & biomimetics
The aye-aye (Daubentonia madagascariensis) is best known for its unique acoustic-based foraging behavior called 'tap-scanning' or 'percussive foraging'. The tap-scanning is a unique behavior allowing aye-aye to locate small cavities beneath tree bark...

Artificial intelligence as an analytic approximation to evaluate associations between parental feeding behaviours and excess weight in Colombian preschoolers.

The British journal of nutrition
Parental practices can affect children's weight and BMI and may even be related to a high prevalence of obesity. Therefore, the aim of this study was to evaluate the relationship between parents' practices related to feeding their children and excess...

The use of machine learning to detect foraging behaviour in whale sharks: a new tool in conservation.

Journal of fish biology
In this study we present the first attempt at modelling the feeding behaviour of whale sharks using a machine learning analytical method. A total of eight sharks were monitored with tri-axial accelerometers and their foraging behaviours were visually...

Robot-assisted feeding: A technical application that combines learning from demonstration and visual interaction.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: The traditional meal assistance robots use human-computer interaction such as buttons, voice, and EEG. However, most of them rely on excellent programming technology for development, in parallelism with exhibiting inconvenient interaction...