Project SALUS will be conducted through a Work Plan structured in 6 Work Packages over 36 months of project duration. The rationale of the overarching logical thread of the project’s Work Plan is to investigate the social, regulatory, and economic context of LTC needs of the elder and dependent to create adequate flexible technologically supported services to LTC patients and caretakers that are maximally useful, accessible, and adaptable. The activities in the project’s 6 WPs as follows:


Coordination and management. This project-wide WP will include the technical and financial monitoring of the status and progress of the different tasks, their results, the dependencies between them and the implementation of corrective measures in case of any technical deviation appears.


Social, economic, and ethical research of Long-Term Care needs of the elderly and dependent. This WP will investigate through the lens of sociological, economic, and legal research the entire context and needs of Long-Term Care provision of services for elder and dependent people. By means of documented and replicable research methodologies, this will result in the creation of detailed reports that will be of research value on their own while informing further project tasks. Additionally, via this comprehensive LTC context, ethical guidelines for AI-based LTC services in the project, ontological LTC representations, and search mechanisms in healthcare bases will be investigated.


Long-Term Care monitoring with unipersonal Digital Twins and Assisted Living devices. Research on Digital Twin modelling, communication, and simulation to create unipersonal physical and mental health and wellbeing digital twins that virtually mirror LTC patient status and behaviour, sensory devices to feed data to the digital twins (IoP wearables and Ambient sensors to monitor patients their activity), and psychological procedures to assess long-term mental health of LTC patients.


Accessibility of the interaction and usability to improve quality of life for people in Long-Term Care. Research to ensure adoption of the LTC support framework by assessing and improving its usability by LTC patients and care practitioners: inclusive multimodal devices for people with mobility/vision/hearing impairments, interaction modes bettering User eXperience, mechanisms to create dedicated Service-Level Agreements, and psychological methods to assess usability.


Trustworthy Artificial Intelligence for personalized services to dependent people in Long-Term Care. Research on eXplainable deep neurosymbolic models and algorithms to trigger smart alerts for care professionals about the health and activity status of LTC patients, decentralized Mutual Mapping Clustering methods to evaluate the health and quality of LTC services and optimize the assignment of caretakers to patients, hybrid collaborative risk-aware recommender algorithms to recommend physical and mental activities to LTC patients to prevent health problems, and pre-trained autoregressive transformer language models to create virtual conversational assistants to support accompaniment of LTC patients in situation of solitude.


Experimentation on use cases in laboratory conditions of the digital framework for Long-Term Care. This WP will be focused on experimenting in controlled conditions on a set of use cases from the perspective of LTC caregivers and care receivers, to evaluate all the services to support LTC created in the project. The devices, models, algorithms, and components will be refined accordingly, and a roadmap for the future extension and raise of maturity of the framework will be created.