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CORDIS - Resultados de investigaciones de la UE

Cognitive-Networks-Enabled Transnational Proactive Healthcare (CoNHealth)

Final Report Summary - CONHEALTH (Cognitive-Networks-Enabled Transnational Proactive Healthcare (CoNHealth))

People are living longer and healthier lives. In 2006, almost 500 million people worldwide were 65 and older. By 2030, that total is projected to increase to 1 billion - 1 in every 8 of the earth’s inhabitants [1]. This represents one of the greatest achievements of the last century but also a significant challenge. Longer lives must be planned for. The Global Burden of Disease, a study conducted by the World Health Organization and the World Bank, predicts a very large increase in disability caused by increases in age- related chronic disease in all regions of the world. In a few decades, the loss of health and life worldwide will be greater from non communicable or chronic diseases (e.g. cardiovascular disease, dementia and Alzheimer’s disease, cancer, arthritis, and diabetes) than from infectious diseases, childhood diseases, and accidents. If we restrict attention to older ages, chronic diseases already account for more than 87 percent of the burden for the over-60 population in all countries. The critical issue, therefore, is how to mobilize and allocate resources to address chronic diseases across the globe.
Rising healthcare industry costs have created a lucrative opportunity for technology and service providers, as hospitals and other front-line caregivers look to adopt new technology to lower their operating costs. Wireless networks, voice over internet protocol (VoIP) deployments, medical sensors, as well as extending care to remote patients via telemedicine applications all promise to lower healthcare delivery costs. Consider that a group of home-based patients, at high risk for ischemic stroke, are under non-contact, non-invasive, 24-hour monitoring for the coordination and balance of their movements through an information centric sensor network, which consists of sensors, platforms, models, and communication infrastructures that can collectively behave as a single dynamically adaptive system. Subsequently, an intelligent data fusion centre controlling this sensor network will forward the collected physiological data to a personal health information management system (PHIMS) through either wireless communication networks or Internet in a secure, reliable, and efficient manner. Relevant caregivers such as clinics, hospitals, and emergency rooms can access PHIMS to provide prompt diagnosis. It is envisaged that in future such distributed diagnosis and home healthcare should be provided in a transnational context to optimize utilization of limited healthcare resources for ageing population across the globe, and meanwhile enable proactive diagnosis, intervention, and treatment through immediate and automated exchange of information with distant sites. Due to the nature and funding strategy of FP7-PEOPLE-2011-IRSES, the current networking programme does not include actual clinical trials, and hence would not involve research on humans, privacy, or any other ethical issues. The project has been successful. The achievement is beyond expectation although the implemented secondment is less than planned secondment. The main aims are to strengthen research partnerships through staff exchanges and networking activities between Partners. In addition to achieving scientific results in a particular area, the CONHEALTH project is above all expected to create additional benefits for the participants in terms of transfer of knowledge and to generate a basis for sustainable cooperation. The activities within the proposed project are divided into 6 Work Packages. All Work Packages are related and complementary. The proposed project helps to increase the transfer of knowledge between Partners as well as allow to build the basis for long-term cooperation. The major achievements can be summarized as follows:
(1) During the 4-year International Research Staff Exchange Scheme, Completed visits 87.31 months (40% of the original plan) due to lack of overhead fund associated with the allowance;
(2) The project website has been established; All relevant research awards such as publications, patents, discussions and etc are detail lay out.
(3) Two international workshops have been successfully organized as planned, in China by Prof. Yifan Chen, South University of Science and Technology of China and Professor Gui Yun Tian, Newcastle University; and In Italy, by Dr. Lorenzo Mucchi, University of Florence.
(4) More than 80 papers have been published in peer reviewed journals and international conferences; More than 10 patents have been applied. Several research awards, keynotes and invited talks have produced in the consortium;
(5) More than 10 million Euro relevant projects within the research consortium have been successfully granted during the project. The successful grants includes: Newcastle University won EPSRC funded A systematic study of Physical LAyer Network coding: from information-theoretic understanding to practical DSP algorithm design (P.L.A.N). H2020 Innovative Training Networks (ITN-ETN) proposal NDTonAIR has been granted.
(6) A sustainable network has been established. It has been demonstrated not only by the further research grant above, but also increasing the transfer of knowledge between partners and extension of research partners. For example, UNEW has built research links to several other universities in China e.g. University of Electronic Science and Technology of China (UESTC) for wearable sensor networks and healthcare monitoring.
(7) More than 30 RAs, PhD students and Master students have been successful trained in the project.
(8) UNEW has built significant research link with MIT, USA. Professor Kenichi Soga , FRS, Cambridge university, UK has invited Professor Tian for Cambridge Conference on Wireless Sensor Network for Civil Engineering and Infrastructure Monitoring. Professor Tian is also invited for talk in IEEE/CIC International Conference on Communications in China 27-29 July 2016, Chengdu, China.