# Can Semantics Uncover Hidden Relations between Neurodegenerative Diseases and Artistic Behaviors?
## 6 Proposed Approach  
The previous section highlighted the lack of an ES/DSS that uses products of artistic expression, such as paintings, combined with other personal health data to enable the diagnosis and progression of PDs. Therefore, in this section, a framework for the detection of common mechanisms between patients with PD and those who possess artistic talents is proposed (Figure 4). The proposed framework utilizes semantic models based on fuzzy ontologies with the aim of creating an integrated representation of biological and artistic knowledge. To realize this framework, an ontology-based interlinking and decision support system must be developed and evaluated, emphasizing fuzzy semantics and biomedical/bioengineering data. The use of fuzzy semantics accommodates the uncertainty and imprecision often associated with PD and artistic expression, and it can help reveal patterns and connections that may not be initially apparent. Semantics (ontologies) play a critical role in this framework, providing a structured formal and explicit representation of the data and facilitating the identification of relationships between different concepts. Moreover, ontologies are used to link various data sources, leading to a more complete understanding of the relationship between PD and artistic behaviors. The proposed system takes interconnected data and fuzzy semantics as inputs and determines (a) if PD and artistic behavior interrelations exist and (b) if preliminary PD biomarkers are present.  
As previously discussed, few expert systems utilize personal health sensor-based data in order to facilitate the diagnosis and monitoring of PD. Those related works, and the expanding of the ontologies that can annotate and conceptualize sensor data, have influenced the design of the proposed framework. Taking a step further from other frameworks, an additional input for the proposed framework is the data collected through wearable devices during artistic tasks performed by the PD patients. Specifically, an application for smartwatches has already been designed and tested for the purpose of our research. The application enables the collection of movement data from ND patients during artistic  
Figure 4: High-level design of a system realizing the proposed framework for PD patients.  
activities such as drawing. The artistic outputs, drawings, paintings, etc., will be collected via scanning techniques. Therefore, multiple scanning techniques can and will be assessed for suitability with our proposed framework. Finally, PHR data will be injected. All three types of data sources will be semantically annotated using the corresponding semantics of a unified ontological model (which is under development) and RDF-encoded in a personal health knowledge graph (PHKG) for each patient. By combining biomedical/bioengineering data, sensor data (e.g., movement), artistic expression data, and fuzzy semantics, the proposed framework aims to improve the diagnosis and treatment of PDs by providing a more comprehensive understanding of their underlying mechanisms. A CDSS implemented based on the proposed framework is expected to assist in making more complex and accurate clinical decisions, guiding doctors in the diagnosis and in patients' monitoring processes. Ultimately, the proposed framework and the CDSS implementations based on it have the potential to contribute to the development of new therapies and interventions for NDs in general.