Ontological Model in the Identification of Emotional Aspects in Alzheimer Patients

David Ricardo Castillo Salazar; Laura Lanzarini; Héctor Gómez; Saravana Prakash Thirumuruganandham; Dario Xavier Castillo Salazar

doi:10.3390/healthcare11101392

Ontological Model in the Identification of Emotional Aspects in Alzheimer Patients

Healthcare (Basel). 2023 May 11;11(10):1392. doi: 10.3390/healthcare11101392.

Authors

David Ricardo Castillo Salazar^{1

2}, Laura Lanzarini³, Héctor Gómez⁴, Saravana Prakash Thirumuruganandham¹, Dario Xavier Castillo Salazar⁵

Affiliations

¹ Centro de Investigación de Ciencias Humanas y de la Educación (CICHE), Universidad Indoamérica, Ambato 180103, Ecuador.
² Facultad de Informática, Universidad Nacional de la Plata, La Plata 1900, Argentina.
³ Instituto de Investigación en Informática LIDI (Centro CICPBA), Facultad de Informática, Universidad Nacional de la Plata, La Plata 1900, Argentina.
⁴ Centro de Posgrados, Universidad Técnica de Ambato, Ambato 180104, Ecuador.
⁵ Unidad Educativa Las Americas, Area de Ciencias Experimentales, Ambato 180103, Ecuador.

Abstract

The present work describes the development of a conceptual representation model of the domain of the theory of formal grammars and abstract machines through ontological modeling. The main goal is to develop an ontology capable of deriving new knowledge about the mood of an Alzheimer's patient in the categories of wandering, nervous, depressed, disoriented or bored. The patients are from elderly care centers in Ambato Canton-Ecuador. The population consists of 147 individuals of both sexes, diagnosed with Alzheimer's disease, with ages ranging from 75 to 89 years. The methods used are the taxonomic levels, the semantic categories and the ontological primitives. All these aspects allow the computational generation of an ontological structure, in addition to the use of the proprietary tool Pellet Reasoner as well as Apache NetBeans from Java for process completion. As a result, an ontological model is generated using its instances and Pellet Reasoner to identify the expected effect. It is noted that the ontologies come from the artificial intelligence domain. In this case, they are represented by aspects of real-world context that relate to common vocabularies for humans and applications working in a domain or area of interest.

Keywords: Alzheimer; Pellet Reasoner; Protégé; apache netbeans; ontology; semantics; taxonomy.

Grants and funding

All the authors acknowledge financial support from the seed grant “Computational modeling of biomaterials and applications to bioengineering and classical and quantum machine learning for predicting social engineering (2022–2026, code: INV-0014-03-011)”, Universidad Indoamérica, Ecuador, awarded to S.P.T.