Designing a Personalised Case-Based Recommender System for Mobile Self-Management of Diabetes During Exercise

Increasing physical activity for type 1 diabetes patients is associated with physical and mental health benefits. However, the control of blood glucose levels for diabetes requires an effective balance of carbohydrate intake and insulin dosage to maintain a balanced blood glucose level before, during and after exercise. Existing mobile applications lack an intervention module that help users maintain an optimal blood glucose level while performing physical exercise. In this paper, we propose a personalised case-based recommender system for selfmanagement of diabetes during exercise. One key aspect of the proposed recommender system is the recommendation of carbohydrate intake and insulin dosage to users during exercise session using visual representations. We conduct a user study with 10 type 1 diabetes patients focusing on usability of the visual representations and the helpfulness of the recommendation. Preliminary results encourage future work towards the development of a mobile application for patients.