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Content archived on 2024-06-18

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

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.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.

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Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

FP7-PEOPLE-2010-IIF
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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

MC-IIF - International Incoming Fellowships (IIF)

Coordinator

KINGSTON UNIVERSITY HIGHER EDUCATION CORPORATION
EU contribution
€ 279 680,00
Address
HOLMWOOD HOUSE GROVE CRESCENT
KT1 2EE KINGSTON UPON THAMES
United Kingdom

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Region
London Outer London — South Merton
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

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