MARIO is an assistive robot that has to support a set of knowledge-intensive tasks aimed at increasing autonomy and reducing loneliness in people with dementia and supporting caregivers in their activity to assess patients' cognitive status. Examples of knowledge-intensive tasks are the comprehensive geriatric assessment (CGA) and the delivery of reminiscence therapy. In order to enable these tasks, MARIO features a set of abilities implemented by pluggable software applications. MARIO's abilities contribute to and benefit from a common knowledge management framework. For example, the ability associated with the CGA retrieves questions to be posed to the patient from the framework and stores the obtained answers and associated relevant metadata. In this work we presents the MARIO knowledge management software framework, which combines robotics with ontology-based approaches and Semantic Web technologies. It consists of (1) a set of interconnected and modularized ontologies, meant to model all knowledge areas that are relevant for MARIO abilities, and (2) a set of software interfaces that provide high-level access to the ontology network and its associated knowledge base. Finally, we demonstrate how the knowledge management framework supports the applications for CGA and reminiscence therapy, implemented on top of the knowledge base.
Ontology-Based Knowledge Management for Comprehensive Geriatric Assessment and Reminiscence Therapy on Social Robots
Tipo Pubblicazione:
Contributo in volume
Publisher:
Springer, Cham, Heidelberg, New York, Dordrecht, London, CHE
Source:
Data Science for Healthcare, pp. 173–193. Cham, Heidelberg, New York, Dordrecht, London: Springer, 2019
info:cnr-pdr/source/autori:Asprino, Luigi; Gangemi, Aldo; Nuzzolese, Andrea Giovanni; Presutti, Valentina; Reforgiato Recupero, Diego; Russo, Alessandro/titolo:Ontology-Based Knowledge Management for Comprehensive Geriatric Assessment and Reminiscence Th
Date:
2019
Resource Identifier:
http://www.cnr.it/prodotto/i/400228
https://dx.doi.org/10.1007/978-3-030-05249-2_6
info:doi:10.1007/978-3-030-05249-2_6
Language:
Eng