Application of Wearable Devices in Diabetes Management

Abstract

Diabetes mellitus poses a significant global health challenge, impacting hundreds of millions worldwide. Effective management and prevention of complications rely on dynamic, real-time glucose monitoring. This review provides a comprehensive overview of the rapidly evolving landscape of wearable technologies for glucose monitoring and diabetes care, with a focus on cutting-edge advancements and their integration with artificial intelligence (AI) and multi-omics data. We explore diverse glucose monitoring approaches, including continuous glucose monitors (CGMs) and smartwatches, highlighting their contributions to tracking physical activity, food intake, medication adherence, and direct glucose measurements. Our emphasis is placed on the role of AI systems in enabling predictive analytics and personalized care, as well as the integration of wearable data with multi-omics insights—spanning genomics, proteomics, and gut microbiome analyses—to enhance understanding of individual glucose metabolism. Given the challenges of existing methods, such as invasiveness, accuracy, and accessibility, we discuss future directions, including the potential of smart glasses, advanced AI models, and seamless data integration, to revolutionize diabetes management. This review offers valuable insights into how wearable technologies, AI, and multi-source data analysis are shaping the future of precision diabetes care.