The emergence of eating disorders and obesity as major health concerns increased research in these fields. However, impressive advances in neurobiology, genetics and sociology of eating had minor clinical or sociological impact. In obesity, pharmacological interventions have failed and while life-style interventions seem moderately successful, they are embedded in specific social contexts. In the field of eating disorders traditional interventions have poor results and high levels of relapse. Our central assumption, validated in randomized control trials, is that supervised training of patients to eat and move in a non-pathological way is effective in the prevention of both eating disorders and obesity. The logical next step is to apply the same kind of methodologies to the general population, in real life by combining expertise in identifying and modifying behavioural patterns with current technical advancements in the fields of sensors and intelligent systems. SPLENDID aims to develop a Personalised Guidance System to help and train children and young adults to improve their eating and activity behaviour by detecting subjects at risk for developing obesity or eating disorders and offering them enhanced monitoring and guidance in order to prevent further disease progression. To this end it will monitor key parameters of eating and activity, such as food intake, meals structure, snacking, daily physical activity during real life; evaluate in real-time and offer guidance towards recommended behaviours. Four studies in Sweden and Netherlands will evaluate:(i)a screening programme conducted at school settings during daily meals, with the aim to assess the children''s eating behaviour, and (ii)the capability of the system to offer correct and effective guidance on eating/activity behaviour. The incorporation of a school, a healthcare provider and a technology provider in the consortium maximises the potential for successful business model definition and exploitation.
|Effective start/end date||1/10/13 → 30/09/16|
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.