Commercial indoor spaces such as hospitals, hotels, offices offer great potential for commercial exploitation of logistic robotics. Also, offer advantages for their deployment, since they are required by law to meet stringent building codes, and therefore the navigation space exhibits some structure. In addition, they offer reliable communications infrastructure, since this is required for normal business operation. Thus, commercial spaces are rightfully considered the next great field of logistic robotics deployment. Despite these advantages, today, few solutions exist, and these solutions do not trigger widespread acceptance by the market. This is because existing systems require costly infrastructure installation (arrays of peripheral sensors, mapping, etc.); they do not easily integrate to corporate IT solutions and as a result, they do not fully automate procedures and traceability; they are limited to a single type of service, i.e. transfer of goods. Through transfer of knowledge, multidisciplinary research and cross-fertilization between academia and industry, ENDORSE will address the aforementioned technical hurdles. Four innovation pillars will be pursued: (i) infrastructure-less multi-robot navigation, i.e. minimum (if any) installation of sensors and communications buses inside the building for the localization of robots, targets and docking stations; (ii) advanced HRI for resolving deadlocks and achieving efficient sharing of space resources in crowded spaces; (iii) deployment of the ENDORSE software as a cloud-based service facilitating its integration with corporate software solutions such as ERP, CRM, etc.; (iv) reconfigurable and modular hardware architectures so that diverse modules can be easily swapped. The latter will be demonstrated and validated by the integration of an e-diagnostic support module (equipped with non-invasive sensors/devices) and the Electronic Health Records (EHR) interfacing, which will serve as an e-diagnostic mobile station

Advances in robotics and artificial intelligence hold a promise for the radical transformation of healthcare services. Besides, the COVID-19 pandemic demonstrates that robots are crucial allies during pandemics. Yet, the adoption of these technologies is impeded by concerns related to cybersecurity issues. The rise of security incidents is a timely reminder that not only the volume of attacks is increasing but their diversity is also expanding, posing a significant threat towards disrupting clinical care delivery. Ongoing research focuses on the use of robotics operating in healthcare spaces (surgical, service, logistics), while security aspects are not well covered in the research community. RESPECT project objective is to create a sustainable European and inter-sectoral network of organisations working on a joint research programme aiming to design and develop concrete defense strategies to ensure secure, safe, resilient and privacy-preserving operation of indoor mobile robotics solutions for logistic applications in healthcare environments. Specifically the main research objectives of the project are: (i) Explore and identify system-specific cyber-physical weaknesses posing security, privacy, and safety threats, in autonomous mobile robots operating in a healthcare environment; (ii) Analyse surfaced vulnerability issues in conjunction with projected threats and propose defence measures and mitigation strategies towards safeguarding mobile robots operation. (iii) Define and standardize a minimal set of vulnerability testing procedures and guidelines leveraging and extending the Robot Vulnerability Scoring System for safe and autonomous robotic fleet management in a “safety-critical setting”. The project will be implemented through staff exchanges among different organizations with complementary expertise in cybersecurity, healthcare, cloud computing and robotics from 5 countries across EU promoting transfer of knowledge between industry and academia.

Parkinson's disease (PD) is a movement disorder characterized by muscle rigidity, tremor, physical movement slowing and in extreme cases, loss of physical movement. Primary symptoms result of decreased motor cortex stimulation caused by insufficient dopamine formation in the brain’s dopaminergic neurons. Secondary symptoms include high level cognitive dysfunctions and subtle language problems. PD is chronic and progressive. Currently there is no cure for PD and associated costs, in terms of quality of life and health and social care expenditures, are expected to rise as the population ages. As none of the existing PD interventions has been really effective the field shows potential for the development of systems to monitor individuals and facilitate symptoms’ management. The design of efficient ICT management system integrating remote monitoring of multi-parametric factors, decision support for medical staff, personalized and adaptable care, and patient and family education is a viable solution. PROPHETIC will exploit modern smart miniaturized systems and advanced information systems towards an infrastructure for remote, continuous, noninvasive acquisition and advanced processing of multi-parametric data and friendly telecare provision based on serious gaming. It will use embedded electronics (suite and cap) capable of measuring neural, psychological, physiological, and biomechanical parameters, and securely communicating them to a Medical Business Intelligence System where pre-processed data will be further analysed hence overcoming real time activity monitoring limitations. Continuous monitoring while aware of the patient’s levodopa medication will help determine health and motor status and avoid levodopa side effects e.g. dyskinesia, freezing, low blood pressure, and falls. It will support caregivers’ decisions and allow early interventions. Appropriate information could be shared between the actors through e.g. smart phones with access according to their role.

It is a fact that the European population growth is slowing down, while the population ageing accelerates. Rapid increases in the elderly population are predicted for the coming decades due to the ageing of post-war baby births. Within Europe’s ageing population, Hearing Loss, Cardio Vascular Diseases, Cognitive Impairments, Mental Health Issues and Balance Disorders, as well as Frailty, are prevalent conditions, with tremendous social and financial impact. Preventing, slowing the development of or dealing effectively with the effects of the above impairments can have a significant impact on the quality of life and lead to significant savings in the cost of healthcare services. Digital tools hold the promise for many health benefits that can enhance the independent living and well-being of the elderly. Motivated by the above, the aim of the SMART BEAR platform is to integrate heterogeneous sensors, assistive medical and mobile devices to enable the continuous data collection from the everyday life of the elderly, which will be analysed to obtain the evidence needed in order to offer personalised interventions promoting their healthy and independent living. The platform can also be connected to hospitals and other health care service systems to obtain data of the end-users (e.g., medical history) to be considered in making decisions for interventions. SMART BEAR will leverage big data analytics and learning capabilities, allowing for large scale analysis of the above mentioned collected data, to generate the evidence required for making decisions about personalised interventions. Privacy-preserving and secure by design data handling capabilities, covering data at rest, in processing, and in transit, will cover comprehensively all the components and connections utilized by the SMART BEAR platform. The SMART BEAR solution will be validated through five large-scale pilots involving up to 4.100 elderly living at home in Greece, Italy, France, Portugal and Romania.