Ontology-based decision support systems for diabetes nutrition therapy: A systematic literature review.

Diabetes is a non-communicable disease that has reached epidemic proportions, affecting 537 million people globally. Artificial Intelligence can support patients or clinicians in diabetes nutrition therapy - the first medical therapy in most cases of Type 1 and Type 2 diabetes. In particular, ontology-based recommender and decision support systems can deliver a computable representation of experts' knowledge, thus delivering patient-tailored nutritional recommendations or supporting clinical personnel in identifying the most suitable diet. This work proposes a systematic literature review of the domain ontologies describing diabetes in such systems, identifying their underlying conceptualizations, the users targeted by the systems, the type(s) of diabetes tackled, and the nutritional recommendations provided. This review also delves into the structure of the domain ontologies, highlighting several aspects that may hinder (or foster) their adoption in recommender and decision support systems for diabetes nutrition therapy. The results of this review process allow to underline how recommendations are formulated and the role of clinical experts in developing domain ontologies, outlining the research trends characterizing this research area. The results also allow for identifying research directions that can foster a preeminent role for clinical experts and clinical guidelines in a cooperative effort to make ontologies more interoperable - thus enabling them to play a significant role in the decision-making processes about diabetes nutrition therapy.

A Knowledge-based Decision Support System for recommending safe recipes to individuals with dysphagia.

BACKGROUND: Dysphagia is a disorder that can be associated to several pathological conditions, including neuromuscular diseases, with significant impact on quality of life. Dysphagia often leads to malnutrition, as a consequence of the dietary changes made by patients or their caregivers, who may deliberately decide to reduce or avoid specific food consistencies (because they are not perceived as safe), and the lack of knowledge in how to process foods are critics. Such dietary changes often result in unbalanced nutrients intake, which can have significant consequences for frail patients. This paper presents the development of a prototypical novel ontology-based Decision Support System (DSS) to support neuromuscular patients with dysphagia (following a per-oral nutrition) and their caregivers in preparing nutritionally balanced and safe meals. METHOD: After reviewing scientific literature, we developed in collaboration with Ear-Nose-Throat (ENT) specialists, neurologists, and dieticians the DSS formalizes expert knowledge to suggest recipes that are considered safe according to patient's consistency limitations and dysphagia severity and also nutritionally well-balanced. RESULTS: The prototype can be accessed via digital applications both by physicians to generate and verify the recommendations, and by the patients and their caregivers to follow the step-by-step procedures to autonomously prepare and process one or more recipe. The system is evaluated with 9 clinicians to assess the quality of the DSS's suggested recipes and its acceptance in clinical practice. CONCLUSIONS: Preliminary results suggest a global positive outcome for the recipes inferred by the DSS and a good usability of the system.

Proposal for an ICF-based methodology to foster the return to work of persons with disability.

BACKGROUND: Employment is an essential component of life as it provides income, sense of engagement and opportunities for personal development. Unemployment due to disability following an accident may have dramatic social and psychological consequences on individuals; it is thus fundamental to foster return to work of these persons. OBJECTIVE: The present work was aimed to develop a methodology determining suitable jobs for people living with disability after a job-related accident. METHODS: The Occupational Information Network (O*NET) taxonomy was combined with the International Classification of Functioning, Disability and Health (ICF) to match individual resources with specific job requirements. ICF Linking Rules were employed by two independent groups of researchers to associate ICF codes to O*NET skill and ability descriptors. RESULTS: O*NET descriptors were linked to 92 unique ICF codes. A "Criticality score" combining ICF and O*NET features to assess suitability of selected jobs for persons with disabilities was also proposed. CONCLUSIONS: The proposed methodology represents a novel instrument to support return to work; the capability to assess specific work-related facets through the lens of both the ICF model and O*NET taxonomy would conceivably provide vocational rehabilitation specialists and occupational therapists with a useful tool fostering job placement of workers with disability.

E-Cabin: A Software Architecture for Passenger Comfort and Cruise Ship Management.

A cruise ship is a concentrate of technologies aimed at providing passengers with the best leisure experience. As tourism in the cruise sector increases, ship owners turned their attention towards novel Internet of things solutions able, from one hand, to provide passengers with personalized and comfortable new services and, from the other hand, to enable energy saving behaviors and a smart management of the vessel equipment. This paper introduces the E-Cabin system, a software architecture that leverages sensor networks and reasoning techniques and allows a customized cabin indoor comfort. The E-Cabin architecture is scalable and easily extendible; sensor networks can be added or removed, rules can be added to/changed in the reasoner software, and new services can be supported based on the analysis of the collected data, without altering the system architecture. The system also allows the ship manager to monitor each cabin status though a simple and intuitive dashboard, thus providing useful insights enabling a smart scheduling of maintenance activities, energy saving, and security issues detection. This work delves into the E-Cabin's system architecture and provides some usability tests to measure the dashboard's efficacy.

Cabin as a Home: A Novel Comfort Optimization Framework for IoT Equipped Smart Environments and Applications on Cruise Ships.

The international tourism competition poses new challenges to the cruise sector, such as the achievement of the tourists' satisfaction and the increase in on board comfort. Moreover, the growing sophistication of tourists' needs leads to a more user-centric touristic offer. Consequently, a personalized cabin environment, which fits the users' activities and their characteristics, could be a plus value during the cruise vacation. These topics, however, are strictly connected with the diffusion of digital technologies and dynamics, which represent the tools to achieve the goal of a customized on-cruise experience. This paper presents E-Cabin, a novel Internet of Things (IoT) framework architecture that has at its core a reasoning system tuned on data gathered from the environment and from each specific passenger and the activities he/she performs. The framework leverages on knowledge representation with ontologies and consists of a publisher⁻subscriber communication framework that allows all of the IoT applications to use the reasoner and the provided ontologies. The paper demonstrates the proposed system in a demo cruise cabin where, by using the E-Cabin application, it is possible to set various atmospheres based on the users and activities occurring in the cabin.

A Social Virtual Reality-Based Application for the Physical and Cognitive Training of the Elderly at Home.

Frailty is a clinical condition affecting the elderly population which results in an increased risk of falls. Previous studies demonstrated that falls prevention programs are effective, but they suffer from low adherence, especially when subjects have to train unsupervised in their homes. To try to improve treatment adherence, virtual reality and social media have been proposed as promising strategies for the increase of users' motivation and thus their willingness to practice. In the context of smart homes, this work presents SocialBike, a virtual reality-based application aimed at improving the clinical outcomes of older frail adults in their houses. Indeed, SocialBike is integrated in the "house of the future" framework and proposes a Dual Task training program in which the users are required to cycle on a stationary bike while recognizing target animals or objects appearing along the way. It also implements the possibility of training with other users, thus reducing the risk of social isolation. Within SocialBike, users can choose the multiplayer mode they prefer (i.e., collaborative or competitive), and are allowed to train following their own attitude. SocialBike's validation, refinement, and business model are currently under development, and are briefly discussed as future works.

Analysis for the design of a novel integrated framework for the return to work of wheelchair users.

BACKGROUND: Return to work represents an important milestone for workers who were injured during a workplace accident, especially if the injury results in needing a wheelchair for locomotion. OBJECTIVE: The aim of the study was to design a framework for training novice wheelchair users in regaining autonomy in activities of daily living and in the workplace and for providing medical personnel with objective data on users' health and work-related capabilities. METHODS: The framework design was accomplished following the "Usability Engineering Life Cycle" model. According to it, three subsequent steps defined as "Know your User", "Competitive Analysis" and "Participatory Design" have been carried out to devise the described framework. RESULTS: The needs of the end-users of the framework were identified during the first phase; the Competitive Analysis phase addressed standard care solutions, Virtual Reality-based wheelchair simulators, the current methodologies for the assessment of the health condition of people with disability and the use of semantic technologies in human resources. The Participatory Design phase led to the definition of an integrated user-centred framework supporting the return to work of wheelchair users. CONCLUSION: The results of this work consists in the design of an innovative training process based on virtual reality scenarios and supported by semantic web technologies. In the near future, the design process will proceed in collaboration with the Italian National Institute for Insurance against Accidents at Work (INAIL). The whole framework will be then implemented to support the current vocational rehabilitation process within INAIL premises.