An AI‐embedded, Wearable Dual Closed‐Loop Insulin Delivery System for Precision Diabetes Management

Abstract Effective blood glucose management is an increasing demand worldwide. Traditional solutions separate glucose detection and insulin delivery, which is less efficient compared to emerging closed‐loop wearable systems controlled by continuous glucose monitors (CGMs). However, CGM‐controlled systems raise new safety risks, as false CGMs readings can cause insulin overdose, which results in hypoglycemia and fatal consequences. This work proposes a concept of a dual closed‐loop insulin delivery system (DuoLoop) to mitigate the risk issue of CGM‐controlled systems. The first closed‐loop is automated insulin delivery controlled by CGM. The second closed‐loop is the controlled release of glucose‐responsive insulin (GRI), whose release rate depends on actual glucose levels. A customized algorithm is trained and embedded into the wearable CGMs for edge computing. The DuoLoop system shows improved safety in preliminary in vivo test (longer normoglycemia durations, 98.82% vs 92.10%), encouraging its deployment toward precision diabetes care.