The project will consist of targeted research activities undertaken by key individual researchers, supported by Ph.D. students, early-career academics, and professors. The exchanges will enable the reciprocal transfer of knowledge between the members of the consortium and will be deployed by a set of designated activities (visits, trainings, workshops, seminars) open also to external stakeholders. As the consortium comprises members from both industrialized and ICP countries across 3 different continents, the research outputs would benefit the wider population in a worldwide perspective, which can hardly be achieved if each individual partner works alone on this topic.

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 mentioned in Section B5. The research activities undertaken would be completely simulation- oriented and lab-based. Nevertheless, the research outputs generated from CoNHealth would provide critical insight into the design and planning of future clinical trials to be carried out in other full-fledged, large-scale research projects managed by the project partners, which are also deliverables of the current programme.

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 noncommunicable 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 [1]. 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 (see e.g., [2]). 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.

Rapid advances in novel knowledge-based, brain-empowered networking infrastructures are crucial to achieving such TPH [3]-[5]. On one hand, medical sensors would incorporate cognitive wireless connectivity, both short range such as near-field radios to communicate wirelessly to nearby computers, personal digital assistants, or smart-phones, and long range, such as WiFi or cellular communications, to communicate directly with cloud computing services. Such wireless connections permit sensor measurements to be sent to remote caregivers while patients go through their daily life, thus heralding an age of ubiquitous real-time medical sensing. On the other hand, the learning and adaptation capabilities of a cognitive network platform for health monitoring such as vital-sign and motion sensing would facilitate proactive disease management and diagnosis before patients suffer serious complications. Nevertheless, actualizing the potential of CoNHealth requires addressing a multitude of technical challenges. Specifically, healthcare applications impose stringent requirements on system reliability, quality of service, and particularly privacy and security. We attempt to confront these challenges in this project.

[1] National Institute on Aging, National Institutes of Health, U.S. Department of Health and Human Services, U.S. Department of State, Why Population Aging Matters: A Global Perspective, Summit on Global Aging, Mar. 15, 2007.

[2] J. Ko, C. Lu, M. B. Srivastava, J. A. Stankovic, A. Terzis, and M. Welsh, “Wireless sensor networks for healthcare,” Proceedings of the IEEE, vol. 98, no. 11, pp. 1947-1960, Nov. 2010.

[3] J. Mitola, “Cognitive radio architecture evolution,” Proceedings of the IEEE, vol. 97, no. 4, pp. 626-641, Apr. 2009.

[4] S. Haykin, “Cognitive radar: A way of future,” IEEE Signal Processing Magazine, vol. 23, pp. 30-40, Jan. 2006.

[5] S. Maleki, A. Pandharipande, and G. Leus, “Energy-efficient distributed spectrum sensing for cognitive sensor networks,” IEEE Sensors Journal, vol. 11, no. 3, pp. 565-573, Mar. 2011.