## 3 Results
### PANDORA Chatbot  
In order to implement a CA that complies with the PANDORA Motivation Model presented in Section 3.1, the following key requirements were identified:  
1. Allowing users to interact by entering text or using voice commands. 2. Providing responses that users can read or listen to. 3. Guiding PwPD through their exercises. 4. Using the European Portuguese language. 5. Using simple language, with short sentences and common terms. PANDORA is specified using the set of parameters proposed by [PERSON] et al. [12], as summarized in Table 2, to facilitate a more straightforward comparison with other healthcare CAs. Figure 3 illustrates the conceptual architecture of PANDORA. The user interacts with PANDORA using the ONParkinson mHealth app. First, the user's message is transmitted \begin{table}
\begin{tabular}{l l} \hline \hline
**Parameter** & **Specification** \\ \hline Type of Technology & Service delivered via an Android mobile application \\ \hline Dialogue Management & Agent-based \\ \hline Dialogue Initiative & User leads the conversation \\ \hline Input Modality & Written and spoken (Portuguese language) \\ \hline Output Modality & Written and spoken (Portuguese language) \\ \hline Task-Oriented & No (the system is not directed to the short-term achievement of a specific end-goal) \\ \hline Health Domain & Neurology (Parkinson’s Disease) \\ \hline Purpose & Support, Education and Motivation \\ \hline Languages Supported & European Portuguese \\ \hline \hline \end{tabular}
\end{table} 
Table 2: PANDORA chatbot specifications. from the ONParkinson mobile app to the ONParkinson server. From there, it is forwarded to the Dialogflow platform, where the Natural Language Processing (NLU) Unit and the Dialogue Manage process the user input. The Dialogue Manager triggers the generation of a response, which often includes custom tags used to identify specific information required in the text or actions not accessible through Dialogflow. The ONParkinson server receives the response and forwards it to the ONParkinson mobile app. Before reaching the user, the message undergoes treatment and refinement in PAN-DORA's Knowledge units. These Knowledge units can perform automatic actions based on detected patterns. Upon arrival at the ONParkinson mobile app, the Knowledge units analyze and process the message, providing PANDORA with contextual knowledge such as the user's exercise program or current exercise. The knowledge base is divided into two units: the Book of Physiotherapy Terms and the Book of Commands. The Book of Physiotherapy Terms is responsible for analyzing the message text of the user to detect customized tags and match them with a conversion dictionary. The conversion dictionary maps the custom tags to attribute names. For example, the tag \"cnumber repetitions\" is mapped to the attribute \"numberOfRepetitions\". The Book of Physiotherapy Terms replaces the tag with the corresponding attribute value in the message text. On the other hand, the Book of Commands analyzes the user message text to detect custom action tags. Similarly to the book of physiotherapy terms, the book of commands maps action tags to attribute names. However, rather than replacing these tags within the message text, the Book of Commands removes them and generates a set of actions for the application to execute later. Additionally, PANDORA incorporates four distinct Portuguese language voice profiles obtained through Google Text-to-Speech services, consisting of two male and two female voices. We illustrate how PANDORA works and aligns with the proposed motivation model through three user interaction examples (see Figure 4a,b as examples of PANDORA integration in the mHealth app):  
Figure 3: Conceptual architecture of the PANDORA system, depicting its core components and their interactions. * **Skipping Exercise**: The PwPD user asks PANDORA chatbot to skip the current exercise and continue with the program.