Personalised nutritional health assistant

Abstract

The task of creating a personalised health assistant, a chatbot, for individuals with Coeliac Disease is believed to be beneficial for individuals in pursuit of accurate data and those diagnosed with coeliac disease (CD). This condition is a chronic autoimmune disorder triggered by gluten consumption, a protein found in wheat, barley, and rye [1]. It affects 1 in 100 people worldwide, with the only treatment available to date being the recommendation to follow a gluten-free diet [2]. This work researched and subsequently applied recent advances in chatbots to the health sector. Following an in-depth analysis of numerous state-of-the-art models and techniques, a system was implemented to achieve the goal of successfully creating a chatbot that would process and simulate human conversation by answering various questions about Coeliac Disease. This was done using the RASA tool, an API and an LLM. Thus, this chatbot could connect individuals to relevant resources and answer their questions, including whether a product is gluten-free, which could be beneficial to them on a daily basis. Error handling proved to be the biggest challenge of this implementation, primarily due to limitations in the free versions of specific systems. The research and the implementation of the proposed method were evaluated through qualitative and quantitative means. The assessment focused on the system’s performance, including the chatbot’s usability, effectiveness, and user satisfaction. Regarding the user satisfaction and usability part, the majority of the participants evaluating the proposed chatbot confirmed that this chatbot is helpful and provided feedback regarding possible future work. Further, this chatbot’s ability to provide timely and accessible information and support can help users and their condition, aiding them in making informed choices about their diet and lifestyle.