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Smart Big Data Platform to Offer Evidence-based Personalised Support for Healthy and Independent Living at Home

Periodic Reporting for period 1 - SMART BEAR (Smart Big Data Platform to Offer Evidence-based Personalised Support for Healthy and Independent Living at Home)

Reporting period: 2019-09-01 to 2021-04-30

The European population growth is slowing down, while population ageing accelerates. The old-age dependency ratio is projected to increase from 28.8% to 51.6% between 2015 and 2060 and in parallel, due to the slightly declining proportion of children, the total age dependency ratio is projected to rise from 53.2% in 2016 to 79.7% in 2080.
Hearing loss, cardiovascular diseases, cognitive impairments, balance disorders and mental health conditions are amongst the ten most prevalent health challenges that people over 65 experience. These conditions, along with the prevalence of frailty in this age group, lead to a deteriorated quality of life (e.g. inactive lifestyle, isolation, loneliness) and life threats (e.g. physical injury, death, self-harm).
The management of the above conditions by healthcare systems is characterised by high and rising costs as well as gaps in quality, safety, equity and access. These trends are putting significant pressure on age-related public expenditure in the EU, which is estimated that, by 2060, will reach 12.9% of gross domestic product for pensions, 8.3% for health care and up to 3.4% for long-term care.
Digital tools hold promise for many health benefits that can enhance the independent living and well-being of the elderly. Such technologies can facilitate the monitoring of patients’ activities and enable healthcare services at home. They improve the quality of the elder population's well-being in a non-obtrusive way, allowing greater independence, maintaining good health, preventing social isolation for individuals and delaying their placement in institutions such as nursing homes and hospitals. Yet, their use is often perceived to have technological and privacy risks.
The Smart Bear (SB) project will provide a digital solution for sustaining and extending healthy and independent living by implementing an affordable, accountably secure and privacy-preserving platform to support the healthy and independent living of elderly people. This will be achieved through intelligent, evidenced-based interventions on lifestyle, medically significant risk factors and chronic disease management, enabled by the utilisation of continuous and objective medical and environmental sensing, assistive technologies and big data analytics.
SB will deliver a solution offering: i) Continuous and objective monitoring and interventions for precise and personalised medicine towards optimising disease and associated risks’ management; ii) Measurable improvements to the quality of life of the elderly and their ability to live independently. The SB solution will integrate off-the-shelf smart consumer and medical devices to provide a “connected health environment”, an affordable, user-friendly, and secure and privacy-preserving service to the elderly, and increase the efficiency of healthcare delivery and reduce resource waste.
Five pilots, spanning six different countries and 5.000 individuals, will enable the evaluation of the platform in the context of healthcare service delivery by private and public providers at regional, state and EU levels, and demonstrate its efficacy, extensibility, sustainability and cost-effectiveness for the individual and the healthcare system.
Following the outcome of the user requirements analysis and the identification of devices that suit the SB purpose, the main effort was on the delivery of the backbone infrastructure and e-services to support the management and analysis of the data (i.e. produced via sensors/devices, medical record inputted during the recruitment). Based on a tried-and-tested architecture (used in the EVOTION EU project), the SB Architecture has been extended and adapted, where required, to address the specific needs and requirements of SB and its users, and to allow m2m synergies with other H2020 projects. Upon this plateau, initial versions of core SB components and instruments have been developed and scheduled to be tested during a Pilot of Pilots stage (Madeira Island, summer of 2021).
Adhering to the “Privacy by Design” principle, the SB@Cloud integrates state-of-the-art security and privacy methods and technologies that guarantee a good level of privacy for personal data, a status that will be continuously monitored. In parallel, to address heterogeneity in the data and lack of shared semantics across sources, SmartBear leveraged the HL7 FHIR standard and the SNOMED-CT for semantic enrichment of the data with a focus on clinical knowledge modelling. The FHIR SB@Repository will also receive, via secure m2m transmission channels, medical/usage data from the Smart4Health and HoloBalance H2020 projects, with structures suitable for combined AI analytics.
The strategy adopted, compatible with the openness of the SB architecture, will allow the reusability of usage/medical data in the case of common study participants, ensuring additional Covid-19 safety and monitoring, and possibly newly analytics derived from the additional clinical requirements, even after the end of the project. Supplementary to the technical dimension, an initial Data Management Plan, and a Dissemination and Exploitation Plan have been defined.
The SB ambition is driven by five overarching strategic goals:
1) Efficient and privacy-preserving integration of heterogeneous IoT devices, systems and technologies to the SB ecosystem and efficient real-time data streaming;
2) The deployment of a backbone infrastructure based on open standards and a modular design, capable of interoperating real-time with IoT platforms, able to evolve to accommodate technological changes and emerging IoT standards that may emerge in the future, and to handle the storage and in-depth analysis of the data;
3) To provide means for reasoning with uncertain knowledge to gain insights into historical data and predict future situations or to detect abnormalities in the data that may trigger further investigation, and in the end to support the personalised decision support;
4) To address security and privacy concerns by adopting the “Privacy by Design” principle;
5) To capitalise on all previous outcomes with the provision of user-friendly e-services and AI-Explainability features, which will enhance users’ trust in the system and facilitate research and innovation in the field of personalised medicine towards optimising disease and associated risks’ management.
The infrastructure will enable the runtime management and adaptation of data collected to accommodate the needs of users and consider the users’ context, and the extraction of high-level representations by temporal abstractions of data to effectively track the short- and long-term aspects of user behavioural characteristics by exploring associations with past episodes (what, when, how). The infrastructure has been developed by using open standards and a modular design based on the Privacy by Design principle of GDPR, which aims to act as a catalyst for enhancing care coordination by improving the overall knowledge of both professionals and patients, and the communication between those actors. The application of artificial intelligence algorithms to datasets will foster the production of statistical inferences at the level of the individual rather than the group of patients, provide a testbed for correlating well-known clinical evidence on appropriate treatments and machine learning outcomes, for the complex profile of SB target group, improving the quality of care provided.
Pilot of the Pilots in Madeira - presentation event
Pilot of the Pilots in Madeira - stand
Pilot of the Pilots in Madeira - stand