Coordinatore | KINGSTON UNIVERSITY HIGHER EDUCATION CORPORATION
Organization address
address: RIVER HOUSE HIGH STREET 53-57 contact info |
Nazionalità Coordinatore | United Kingdom [UK] |
Totale costo | 279˙680 € |
EC contributo | 279˙680 € |
Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
Code Call | FP7-PEOPLE-2010-IIF |
Funding Scheme | MC-IIF |
Anno di inizio | 2012 |
Periodo (anno-mese-giorno) | 2012-01-16 - 2014-01-15 |
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KINGSTON UNIVERSITY HIGHER EDUCATION CORPORATION
Organization address
address: RIVER HOUSE HIGH STREET 53-57 contact info |
UK (KINGSTON UPON THAMES) | coordinator | 279˙680.00 |
Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.
'One of the key advances in recent healthcare technology innovations has been in the emerging mobile and network technologies for disease management, especially chronic diseases and diabetes in particular. The sharp increase of obesity linked with Type-1 diabetes in children and young population is becoming alarming in the UK and the European countries in general. Most of current projects and research studies that address self-management of diabetes and obesity focus on the functionality, technological and mobility issues but not on behavioural changes and acceptability challenges of these systems. To date, there is no study that addresses these major challenges and issues relating to the patients' adaptability (especially the younger population) with their health carers toward their self-diabetes management using emergent ICT technologies. This problem is more acute in diabetic and obese patients that do not adhere to their medications and in need of emotional support to maintain a more effective healthy behaviour (e.g. diet, exercise, medication compliance, etc.). This project will aim to research, design and develop a new and innovative platform and tools using a combination of long-term evolution wireless technologies linked with interactive robotic coaching technologies and intelligent decision support machines. Novel prediction and decision support algorithms based on reality health data mining, context awareness and artificial intelligence will be developed. These algorithms will then be used to process the information collected from the patients, via their in-home and mobile devices, and provide the necessary adaptable changes of the behavioural and medications preferences for the patients according to their individual needs. A prototype system which incorporates all these emerging technologies will be developed and its performance will be evaluated with the collaborating medical NHS partners in the UK and other European collaborating institutes.'
An EU study investigated diabetes self-management in adolescents using a remote e-health interface. The trial found high acceptance of the system among patients, highest among the youngest group, and no real difference between sexes.
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