A novel hand-held interface supporting the self-management of Type 1 diabetes
This addresses the problem of diabetes management for patients with Type 1 diabetes, but it appears incremental as it builds on existing clinical and interaction requirements.
The paper tackled the problem of self-management for Type 1 diabetes by designing a hand-held interface that allows users to explore predicted short-term relationships between meals, blood glucose levels, and insulin dosages, enabling informed food and exercise decisions, with the design being implemented prior to a clinical trial.
The paper describes the interaction design of a hand-held interface supporting the self-management of Type 1 diabetes. It addresses well-established clinical and human-computer interaction requirements. The design exploits three opportunities. One is associated with visible context, whether conspicuous or inconspicuous. A second arises from the design freedom made possible by the user's anticipated focus of attention during certain interactions. A third opportunity to provide valuable functionality arises from wearable sensors and machine learning algorithms. The resulting interface permits ``What if?'' questions: it allows a user to dynamically and manually explore predicted short-term (e.g., 2 hours) relationships between an intended meal, blood glucose level and recommended insulin dosage, and thereby readily make informed food and exercise decisions. Design activity has been informed throughout by focus groups comprising people with Type 1 diabetes in addition to experts in diabetes, interaction design and machine learning. The design is being implemented prior to a clinical trial.