BackgroundFalls in older people represent a major age-related health challenge facing our society. Novel methods for delivery of falls prevention programs are required to increase effectiveness and adherence to these programs while containing costs. The primary aim of the Information and Communications Technology-based System to Predict and Prevent Falls (iStoppFalls) project was to develop innovative home-based technologies for continuous monitoring and exercise-based prevention of falls in community-dwelling older people. The aim of this paper is to describe the components of the iStoppFalls system.MethodsThe system comprised of 1) a TV, 2) a PC, 3) the Microsoft Kinect, 4) a wearable sensor and 5) an assessment and training software as the main components.ResultsThe iStoppFalls system implements existing technologies to deliver a tailored home-based exercise and education program aimed at reducing fall risk in older people. A risk assessment tool was designed to identify fall risk factors. The content and progression rules of the iStoppFalls exergames were developed from evidence-based fall prevention interventions targeting muscle strength and balance in older people.ConclusionsThe iStoppFalls fall prevention program, used in conjunction with the multifactorial fall risk assessment tool, aims to provide a comprehensive and individualised, yet novel fall risk assessment and prevention program that is feasible for widespread use to prevent falls and fall-related injuries. This work provides a new approach to engage older people in home-based exercise programs to complement or provide a potentially motivational alternative to traditional exercise to reduce the risk of falling.

Patients with diabetes were enrolled into a telemonitoring programme. They were offered the choice of collecting their health data either by using Near Field Communication (NFC) enabled mobile phones equipped with a dedicated application (App), or by means of a web-browser based user interface (Web). At the end of the study, each patient was categorized as belonging to either the App or Web group, based on the proportion of data they had transmitted using each method. Of the 403 patients, there were 291 in the App group and 112 in the Web group. The two groups were similar in their demographics, except for gender distribution where 68% of men preferred using the App method in contrast to 95% for women (P < 0.001). Kaplan-Meier analysis showed a steady decline of the compliance rate for both groups, at a similar rate during the first year. It also showed a more rapid decline of the compliance rate thereafter for the Web group, which resulted in a significantly higher rate for the App group over the whole observation period (P = 0.03). We conclude that different types of data acquisition technologies may have an important effect on patients' willingness to participate in telehealth programmes in the long-term.

We conclude that predictive modeling can be used to benchmark the importance of different features on the models derived with data from different hospitals. This might help to optimize crucial processes in a specific hospital, even in other scenarios beyond Patient Blood Management.

Abstract. Semantic interoperability is the key technology to enable evolution of the Internet of Things (IoT) from its current state of independent vertical IoT silos to interconnected IoT platform federations. This paper analyzes the possible solution space on how to achieve semantic interoperability and presents ve possible approaches in detail together with a discussion on implementation issues. It presents the H2020 symbIoTe project as an example on how semantic interoperability can be achieved using semantic mapping and SPARQL query re-writing. We conclude that the found approaches together with the proposed technologies have the potential to act as corner stone technologies for achieving semantic interoperability.

Health trends of elderly in Europe motivate the need for technological solutions aimed at preventing the main causes of morbidity and premature mortality. In this framework, the DOREMI project addresses three important causes of morbidity and mortality in the elderly by devising an ICTbased home care services for aging people to contrast cognitive decline, sedentariness and unhealthy dietary habits. In this paper, we present the general architecture of DOREMI, focusing on its aspects of human activity recognition and reasoning.