## 5 Experimental Analysis and Implementation
### Semantic Ontology Development  
Existing research [60; 61], has demonstrated that affective states of human health could be recognized from physiological condition monitoring. In this regard, several recent studies have focused on collecting data on affective health states through wearable sensors. Queen Mary University of London, United Kingdom, and the University of Trento, Italy, in collaboration, have gathered such data and organized them into the AMIGOS [1] and DEAP [3] datasets. Based on this, we develop two ontology models to express health state concepts and their semantic relationships. The first ontology model has been developed to express the domain concepts of diverse affective health states, which is designed as AMIGOS affective states ontology (shown in Figure 14). This ontology contains several concepts about different states of affective conditions such as stress, anger, amusement, etc. Also, it contains concepts such as the severity of these states, healthcare profiles, and sensor input feed. The modeled ontology has been aligned to the base ontology model following a shared data categorizations. The second ontology model (DEAP semantics ontology as shown in Figure 15), also constitutes the concepts on affective health state conditions and their level of severity  
Figure 13: Semantic interoperability implementation setup. based on the diverse data input; however, the concepts are categorized in different hierarchies and the data are semantically expressed differently. The reason for using AMIGOS and DEAP models is to realize the interoperability issues in the healthcare domain, specifically related to heterogeneous models. Figure 14: AMIGOS semantic Ontology Model. Figure 15: DEAP Semantic Ontology Model. The ontology models have been developed through Protege and expressed in RDF format. Protege is an open-source ontology development tool and framework which supports the implementation of intelligent systems. It is backed by a large community of users in academia and corporate [62]. One of the reasons to use Protege is that it provides the facility to develop knowledge-oriented solutions in any domain with much powerful modeling capability. The base ontology model provides a hub for the integration of multiple semantic ontologies to express the concepts of a domain. In this case, the domain of our use case is the affective states of human health. Therefore the base ontology provides an intermediated concepts, data properties and object properties and semantic conditions that satisfy the rules imposed by the shared representation model for the core data and metadata. The semantic base ontology model developed for the affective health states data has been shown in Figure 16. Moreover, the descriptions of the data input from multiple ontologies that are represented into base feature elements have been incorporated in the model, as shown in the RDF code in Figure 17. The implementation of the base ontology model provides an RDF based ontology to incorporate the affective states concept integration for the AMIGOS ontology and DEAP ontology models. To express the shared representation of the ontology concepts, the lexicon dictionaries of affective states [63] has been followed. The semantic alignment process is based on the semantic annotation procedures. In order to perfectly align the concepts and the properties of different domains', annotation of the data with respect to standard ontologies has been achieved. Moreover, to support the interoperability of these different annotation schemes, a common annotation based on the base ontology model has been developed. In this case, to map the annotation of the AMIGOS model to the DEAP model, semantic annotation to the base ontology model through shared data mapping has been performed. The illustration of this annotation model has been demonstrated in Figure 18.  
Figure 16: Base semantic ontology model.