Maramis Christos, Moulos Ioannis, Ioakeimidis Ioannis, Nolstam Jenny, Lekka Irini, Bergh Cecilia, Maglaveras Nicos
Dept. of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Division for Applied Neuroendocrinology, Karolinska Institutet, Stockholm, Sweden.
Stud Health Technol Inform. 2016;224:135-40.
The worldwide extent of obesity and eating disorders (ED) today highlights the necessity for efficient treatment, but also early prevention of eating-related diseases. A promising category of therapeutic and preventive interventions comes from the domain of behavioral informatics (BI), whose purpose is to monitor and modify harmful behaviors - unhealthy eating in the particular case - with the help of information and communication technologies. Smartphones have already shown great promise in delivering such BI interventions in the field of obesity and ED. In fact, plenty of smartphone applications aiming to monitor and support the change of eating behavior with the help of built-in or external sensors have been proposed in the scientific literature. However, to the best of our knowledge, no smartphone application up to date has been designed to collect eating behavior data for the purpose of population screening against obesity or ED. In this work we describe a novel, sensor-enabled smartphone application that captures in-meal behavioral data from multiple subjects in a brief data collection process, with the end goal of recording, in detail, the user's eating style throughout a cooked meal. These data can later be employed for assessing the subjects' risk for obesity or ED. The proposed application has undergone preliminary evaluation with respect to its usability and technical soundness, yielding promising results.
