SEPTON aims to address the gap in the generic technologies and processes referring to the IT network infrastructure with a holistic approach towards reinforcing NMD security within the healthcare centre premises. The project will advance cutting-edge solutions in healthcare cybersecurity targeting the aforementioned health providers and particularly focusing on networked medical devices (NMDs). The SEPTON approach will result in a comprehensive cybersecurity toolkit providing tools and mechanisms to be used in hospitals and care centres for a) the protection of networked medical devices, including wearable and implantable devices, and using techniques such as polymorphism b) the secure and privacy preserving data exchanges between NMDs, utilising techniques such as blockchain, differential privacy and encryption c) behavioural anomaly detection, utilising a cybersecurity analytics framework coupled with machine learning techniques and hardware acceleration for increased performance and d) NMD vulnerability assessment. The usability of the proposed solutions will be tested in a realistic setup via extensive pilot trials, facilitated by the participation of two healthcare organisations

OBJECTIVES: Build on multi-discipline research (e.g., human-centred methodology integrates cognitive models, ergonomics, understanding of worker’s well being) to accelerate how we identify, acquire and exploit skills valued by industry. Get high take-up by early adopters (e.g., in manufacturing). Augment training in situ with live expert guidance, a tacit learning experience and a re-enactment of the expert, in knowledge-intensive environments where effective decision making, often in new situations, has high impact on effectiveness in production. Bring learning content and technical documentation to life via task-sensitive Augmented Reality (AR). Make final products flexible for workplace integration via industry-standard repositories and toolkits. HOW: Wearable TEL platform enhances human abilities to acquire procedural knowledge by providing a smart system that directs attention to where it is most needed. An extensive audit of industry procedures, policies and participatory design methods will define the main facets of the platform. User test cycles will refine prototypes and deliverables. Existing wearable smart devices and sensors will be tailored to provide an innovative solution for content delivery and measurement of user performance. Comparative tests, stakeholders’ review and leading the IEEE AR group will secure high-standard academic and industrial outputs. RELEVANCE to work programme: WEKIT is strongly aligned with EU job/training policies (e.g., Grand Coalition for Digital Jobs). It enhances the industrial value chain, reduces fragmentation/cost and improves efficiencies with impact regarding speed and scale in production. Looking ahead: roadmap shows safe skill pathways for use of TEL in changing industrial landscapes (e.g. smart machine-to-machine (M2M) knowledge-sharing). Smarter products and services will improve workflows, enhancing (re)training of workers whose skill sets need upgrading after ‘Industry 4.0’.

HumAIne will research, develop, validate and promote a novel operating system for Human-AI collaboration, which will enable the development of advanced decision making applications in dynamic, unstructured environments in different industrial sectors. The HumAIne OS will empower AI solution integrators to implement Human-AI collaboration systems that outperform AI systems and humans when working in isolation. HumAIne’s developments will be integrated into a single OS platform, which will coordinate four interwind components offering Active Learning (AL), Neuro-Symbolic Learning, Swarm Learning (SL) as well eXplainable AI (XAI) capabilities. These advanced AI paradigms are ideal for exploiting true Human-AI collaboration since, in each of them, the worker is the key actor with complete control and understanding of the performed operations. AL enables the development of effective Human-in-the-Loop systems that involve humans when AI faces increased uncertainty. Neuro-Symbolic Learning combines DL with semantics and rules to complete highly complex tasks with high accuracy while requiring considerably less training data than current AI models. Advanced XAI models will be made available, providing explanations of models’ predictions while considering the global context instead of just analysing the feature importance of a single AI model. HumAIne’s XAI will provide guidance to humans to enable the timely optimisation of AL and SL models where human participants provide feedback dynamically as well as fine-tuning of Neuro-Symbolic models. The platform will handle various types of structured and unstructured data, including inputs from humans that will be semantically correlated through ontologies, knowledge graphs, and semantic interoperability. HumAIne will complement its platform with complementary resources (e.g., training) and will be build a vibrant community of interested parties around it, to drive exploitation and wider use of the project's results.

The increasing interconnection of technology in healthcare between devices at the physical and cyber levels has transformed these infrastructures into large Health Care Information Infrastructures. Such HCIIs are considered critical and sensitive infrastructures due to their importance for people’s well-being and safety. On the other hand, the evolving digital interconnectivity has also changed the threat landscape, producing a wide range of security and privacy challenges and increasing the danger of potential cybersecurity attacks. The integrated nature introduces new potential entry points for cybersecurity risks. Thus, there is an urgent, pressing need for the Health operators to protect their HCIIs. Efficient situational awareness, incident handling and risk assessment is an important step to acquiring a thorough and common understanding of cyber-attack situations, and is necessary to timely reveal security events and data breaches occurring into HCIIs. Consequently, analysis of incident information is crucial in attempting to detect the presence of a threat, within HCIIs, that has already been detected in other interdependent systems within the same ecosystem. AI4HEALTHSEC proposes a state of the art solution that improves the detection and analysis of cyber-attacks and threats on HCIIs, and increases the knowledge on the current cyber security and privacy risks. Additionally, AI4HEALTHSEC builds risk awareness, within the digital Healthcare ecosystem and among the involved Health operators, to enhance their insight into their Healthcare ICT infrastructures and provides them with capability to react in case of security and privacy breaches. Last but not least AI4HEALTHSEC fosters the exchange of reliable and trusted incident-related information, among ICT systems and entities composing the HCIIs without revealing sensitive corporate details

COMFORTAGE is a joint effort of medical experts (i.e., neurologists, psychiatrists, neuropsychologists, nurses, memory clinics), social scientists and humanists, technical experts (i.e., data scientists, AI experts, robotic experts) and Digital Innovation Hubs to establish a pan European framework for Community-based, Integrated and People-Centric prevention, monitoring and progression managing solutions for age-related diseases and disabilities. The project’s framework will be empowered by a unique combination and integration of: (i) Medical/clinical innovations (e.g., novel approaches to risk factor analysis and personalized prediction, AI-based medical devices, integrated data sources of age-related clinical evidence, and evidence-based Healthcare Technology Assessment (HTA)), (ii) Cutting edge AI innovations (e.g., explainable AI (XAI), secure AI, serious games, Patient Digital Twins, Virtual Assistive technologies) for trusted, accurate, secure and personalized clinical decision making, (iii) Digital Innovation Hubs (e.g. Smart Homes, robotics and Living Labs) to facilitate and promote research activities in the health and wellbeing domain, and (iv) social innovations for promoting innovative views and co-creating new or improved solutions for assistance and improvement of social integration and interaction. COMFORTAGE will facilitate the integration, harmonization, and management of a host of different data sources, including biobanks, cohorts, medical records, longitudinal observational studies, real-world data about patients, as well of alternative secondary data sources, such as sensors, wearables and mobiles in a standardized structure called Holistic Health Records (HHRs). COMFORTAGE will become a catalyst to help prevent, monitor, and manage progression of age-related diseases and disabilities, especially of dementia and frailty, based on high-end research and analysis of the utilization of the aforementioned technologies.