In 2019 the World Health Organization (WHO) declared 2020-2030 the decade of Healthy Ageing. By the end of this decade - in 2030 - the number of people 60 years and older will grow by 56 per cent, from 962 million (2017) to 1.4 billion (2030). By 2050, the global population of older people will be more than double to 2.1 billion.

Ageing leads to a gradual decrease in physical and cognitive capacity, a growing risk of disease, and ultimately, death. Nowadays, at risk of contracting COVID-19, older persons are at a significantly higher risk of mortality and severe disease following infection, with those over 80 years old dying at five times the average rate [1]. In view of this severe situation, their social networks, their access to health services, their profession and their pensions are also sorely threatened [2]. These challenges lead older persons in tackling ongoing health needs that likely require medication and assistance, and requiring routine home-based visits and community care. In this perspective, the vision of the global strategy is to improve health for everyone including older people by developing and adopting sustainable digital health solutions to promote their quality of life and wellbeing.

Towards efficient health and care systems in Europe, the SHAPES project (“Smart and Healthy Ageing through People Engaging in supportive Systems”) aims at building an EU open Platform that integrates smart digital solutions to collect and analyze older persons’ health, environmental and lifestyle information, identify their needs and provide personalized solutions that uphold the individuals’ data protection and trust.

The main objective of the SHAPES project is to increase the efficiency of health care provision across Europe for older persons by creating the first European open Ecosystem that enables the large-scale deployment of a broad range of digital solutions.

Lab of Medical Physics of Aristotle University of Thessaloniki (AUTH) significantly contributes to the EU project SHAPES by supporting and extending independent and healthy living for older persons adapting innovative digital solutions. In specific, the Integrated Health and Social Care Ecosystem Long Lasting Memories Care (LLM Care) ( and Virtual Patient Scenarios/Mobile Virtual Patients will be deployed by varied pilot sites across EU addressed to care receivers and caregivers respectively.


More particular, the Integrated Health and Social Care Ecosystem Long Lasting Memories Care - LLM Care is an integrated ICT platform which combines state-of- the-art mental exercises against cognitive deterioration with physical activity in the structure of an advanced ambient assisted living environment. It incorporates two interoperable components; the Cognitive Training System, based on the BrainHQ ( and the Physical Training System, based on the webFitForAll ( BrainHQ is a specialized software designed to support cognitive exercise in a fully personalized, adaptable training platform, while webFitForAll is an exergaming platform that provides essential physical training to older people aiming to maintain their fitness and well-being, through the use of an innovative and low-cost technological platform.

This integrated solution is a non-medical intervention that facilitates independent living and it is based on recent research that claims the effectiveness of moto-sensory training on older people with cognitive problems or mild dementia [3]. LLM Care is a key element in maintaining physical and functional abilities that reduces the risk of certain health conditions and leads to a better and more independent living of older people [4].


Over the last decade, the Integrated Health and Social Care Ecosystem LLM Care has been recognized as a multidisciplinary coalition scheme comprised of academic/research organizations, health/tech providers, regional policymakers and civil society organizations, created to align user-driven research, innovation, education and training in the field of Active & Healthy Ageing.

Virtual patients, defined as “interactive computer simulations of real-life clinical scenarios for the purpose of health care and medical training, education or assessment” [5] and based on case-based or problem-based learning, have proved to be particularly useful in teaching clinical decision making [6]. Two different types of virtual patients, developed by Lab of Medical Physics of Aristotle University of Thessaloniki (AUTH), are meant to be implemented in SHAPES; i) Virtual Patients Scenarios and ii) Mobile Virtual Patients.

Virtual Patient Scenarios (VPS) and Mobile Virtual Patients (MVP) are branching scenarios that are used extensively in medical education. More specifically, they are problem-based learning activities aiming at supporting caregivers’ skills with regard to the delivery of care to older people. VPS are developed in the Open Labyrinth (, an open-source platform for creating and playing virtual patients, while MVP in the Open Source Framework Drupal. They are considered effective learning tools that facilitate the transfer of real-life challenges in engaging scenarios which mimic the tensions, distractions and uneven issues that make real-life decisions more difficult. In particular, the methodology followed is to provoke the learner to think through a number of solutions or options in order to move forward in the scenario.


The key element for branching scenarios is for the options to be attractive enough to ensure that learners are often drawn to the wrong choice and thus, the cognitive conflict occurred help them reach new knowledge. In this vein, caregivers have the opportunity of interacting with diverse virtual cases and familiarizing themselves with a range of diseases (such as dementia, diabetes, stroke, heart disease, etc.) with the purpose of acquisition proper teaching skills regarding symptoms, diagnosis and treatment. Except for that, VPS are considered as being valuable for caregivers in encouraging decision making, reasoning skills, as well as self-assessment [7].


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[1] Clark, A., Jit, M., Warren-Gash, C., Guthrie, B., Wang, H. H., Mercer, S. W., ... & Checchi, F. (2020). Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study. The Lancet Global Health, 8(8), e1003-e1017.

[2] ILO Spotlight on work statistics, May 2018,

[3] Romanopoulou, E. D., Zilidou, V. I., & Antoniou, P. E. (2015). Spinning off gerotechnology business activities: the LLM care best practice paradigm. In Handbook of Research on Innovations in the Diagnosis and Treatment of Dementia (pp. 426-436). IGI Global.

[4] Bamidis, PD., Fissler, P., Papageorgiou, SG., Zilidou, V., Konstantinidis, EI., Billis, AS., Romanopoulou, E., Karagianni, M., Beratis, I., Tsapanou, A., Tsilikopoulou, G.: Gains in cognition through combined cognitive and physical training: the role of training dosage and severity of neurocognitive disorder. Frontiers in Aging Neuroscience, 7, 152 (2015).

[5] Ellaway, R., Poulton, T., Fors, U., McGee, J. B., & Albright, S. (2008). Building a virtual patient commons. Medical teacher, 30(2), 170-174.

[6] Triola, M., Feldman, H., Kalet, A. L., Zabar, S., Kachur, E. K., Gillespie, C., ... & Lipkin, M. (2006). A randomized trial of teaching clinical skills using virtual and live standardized patients. Journal of general internal medicine, 21(5), 424-429.

[7] Dafli, E., Fountoukidis, I., Hatzisevastou-Loukidou, C., & Bamidis, P. D. (2019). Curricular integration of virtual patients: a unifying perspective of medical teachers and students. BMC medical education, 19(1), 416.