LTE-HEALTH

Long-Term e-Health Evolution for Improving Diabetic Social and Behavioural Change Management

 Coordinatore KINGSTON UNIVERSITY HIGHER EDUCATION CORPORATION 

 Organization address address: RIVER HOUSE HIGH STREET 53-57
city: KINGSTON UPON THAMES
postcode: KT1 1LQ

contact info
Titolo: Ms.
Nome: Bee
Cognome: Tang
Email: send email
Telefono: +44 20 8417 2054
Fax: +44 20 8417 2972

 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

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    KINGSTON UNIVERSITY HIGHER EDUCATION CORPORATION

 Organization address address: RIVER HOUSE HIGH STREET 53-57
city: KINGSTON UPON THAMES
postcode: KT1 1LQ

contact info
Titolo: Ms.
Nome: Bee
Cognome: Tang
Email: send email
Telefono: +44 20 8417 2054
Fax: +44 20 8417 2972

UK (KINGSTON UPON THAMES) coordinator 279˙680.00

Mappa


 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

self    diabetes    decision    behavioural    obesity    algorithms    health    uk    collaborating    technologies    mobile    population    linked    patients    medications   

 Obiettivo del progetto (Objective)

'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.'

Introduzione (Teaser)

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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