Smart contact lens for personalized glucose level sensing and forecasting

This is the authors' abstract. We don't add key points for this paper.

Smart contact lenses (SCLs) can offer continuous tear glucose (TG) monitoring for tracking blood glucose levels. However, prolonged wear of such SCLs can cause discomfort, and glucose responses vary among individuals. Here, we present an integrated glucose monitoring framework that combines SCL-based glucose sensing, personalized computational models, and a user interface. Lyophilization and hydrogel coating enhance enzyme stability and wearing comfort. We developed two different approaches for glucose tolerance screening and personalized forecasting of glucose responses under predefined meal and exercise scenarios, which can classify glucose tolerance status with 90% accuracy and predict TG fluctuations with root-mean-square error (RMSE) below 0.02. These approaches are integrated into a multimodal conversational interface that provides accessibility to personalized glucose analysis and forecasting.