Conference Paper

My-AHA: Middleware Platform to Sustain Active and Healthy Ageing

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... Baquero et al. [12] analyzed ambient intelligence frameworks in terms of their purposes, architecture, used platform, inclusion of component supervision module, and repository sensor handling. Madureira et al. [13] analyzed middleware platforms for active and healthy aging by specifying a set of features that such platforms should have. Marcos-Pablos and García-Peñalvo [14] analyzed care and assistance ecosystems by considering the groups of ecosystems (health, monitoring, social interaction, reminder, rehabilitation), system actors (older people, disabled, patients, relatives, regulatory parties, research, etc.), allowed modifications (add devices, add services, add software, modify any of them), maturity (conceptualization, pilots, deployed), sensor types (if any), health-related standards (if any), etc. Various taxonomies were also created for platforms for older people. ...
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The EU PlatformUptake project’s main goal is to investigate the usage of EU open and partly-open platforms in active and healthy aging (AHA) and ambient-assisted living (AAL) domains, from a software viewpoint. The aim of the project was to provide tools for a deeper interpretation and examination of the platforms, gather user feedback, and use it to improve the state-of-the-art approach in the AHA and AAL domains, and define instructions to enhance the platforms within the recommended order. The emphasis is on the software viewpoint for decision makers. In this paper, we present (i) the PlatformUptake methodology for AHA open platform assessments and its main objectives; (ii) clustering of the analyzed platforms; and (iii) the taxonomies generated from the text descriptions of the chosen platforms. With the use of the clustering tools, we present which platforms could be grouped together due to their similarities. Different numbers of clusters were obtained with two clustering approaches, resulting in the most informative two and four cluster groups. The platforms could be rather neatly presented in this way and, thus, potentially guide future platform structuring. Moreover, taxonomies, i.e., decision trees of platforms, were generated to easily determine each specific platform or to find platforms with the desired properties. Altogether, the computer comprehension of the platforms may be important additions to the human way of dealing with the AHA platforms, influencing future design, publications, related work, and research.
... The M y−AHA, described by Madureira et al. [30], is a multiplatform middleware designed to perfectly integrate different health and active aging solutions, aiming at well-being. According to the authors, the architecture proposed for the M y − AHA is a multi-module system architecture, fully scalable and easily implementable, focusing on helping caregivers and the elderly themselves improve their current condition, considering changes in cognitive, physical, social, and psychological parameters. ...
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The improvement of technological applications focused on the health context is growing. Different types of applications, such as Health Information Systems (HIS), Electronic Health Records (EHR), and e-Health and m-Health applications, are being developed. With the increasing use of technological solutions in this context, there is a need to integrate the data collected, stored, and processed in these systems. However, the heterogeneity of the data is a factor that makes this integration difficult. To mitigate this problem, middleware appears as an option. This paper aims to understand the current state and future trends of middleware for healthcare applications. To do so, we carried out systematic mapping of the literature on middleware for healthcare systems. This Systematic Mapping initially collected 1162 works, which after the execution of its stages, 34 works were selected for careful reading and, as a result, we present answers to the defined research questions, collected from a careful reading of the selected works. Finally, we concluded that, although there are several middleware solutions in the literature, there is no standard among these solutions, and they end up being limited to solving the problem in a specific context in the health area.
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The population is getting old, and the use of technology has improved the quality of life of the senior population. This is confirmed by the increasing number of solutions targeting healthy and active ageing. Such solutions keep track of the daily routine of the elderly and combine it with other relevant information (e.g., biosignals, physical activity, social activity, nutrition) to help identify early signs of decline. Caregivers and elders use this information to improve their routine, focusing on improving the current condition. With that in mind, we have developed a software platform to support My-AHA, which is composed of a multi-platform middleware, a decision support system (DSS), and a dashboard. The middleware seamlessly merges data coming from multiple platforms targeting health and active ageing, the DSS performs an intelligent computation on top of the collected data, and the dashboard provides a user’s interaction with the whole system. To show the potential of the proposed My-AHA software platform, we introduce the My Personal Dashboard web-based application over a frailty use case to illustrate how senior well-being can benefit from the use of technology.
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Introduction Frailty increases the risk of poor health outcomes, disability, hospitalization, and death in older adults and affects 7%–12% of the aging population. Secondary impacts of frailty on psychological health and socialization are significant negative contributors to poor outcomes for frail older adults. Method The My Active and Healthy Aging (My-AHA) consortium has developed an information and communications technology–based platform to support active and healthy aging through early detection of prefrailty and provision of individually tailored interventions, targeting multidomain risks for frailty across physical activity, cognitive activity, diet and nutrition, sleep, and psychosocial activities. Six hundred adults aged 60 years and older will be recruited to participate in a multinational, multisite 18-month randomized controlled trial to test the efficacy of the My-AHA platform to detect prefrailty and the efficacy of individually tailored interventions to prevent development of clinical frailty in this cohort. A total of 10 centers from Italy, Germany, Austria, Spain, United Kingdom, Belgium, Sweden, Japan, South Korea, and Australia will participate in the randomized controlled trial. Results Pilot testing (Alpha Wave) of the My-AHA platform and all ancillary systems has been completed with a small group of older adults in Europe with the full randomized controlled trial scheduled to commence in 2018. Discussion The My-AHA study will expand the understanding of antecedent risk factors for clinical frailty so as to deliver targeted interventions to adults with prefrailty. Through the use of an information and communications technology platform that can connect with multiple devices within the older adult's own home, the My-AHA platform is designed to measure an individual's risk factors for frailty across multiple domains and then deliver personalized domain-specific interventions to the individual. The My-AHA platform is technology-agnostic, enabling the integration of new devices and sensor platforms as they emerge.
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