LoopKit/Loop

Loop is an iOS app template designed to build automated insulin delivery systems for diabetes management. Written in Swift, it functions as a closed-loop artificial pancreas system built on top of the LoopKit framework, which provides the underlying data storage, retrieval, calculation capabilities, and reusable view controller components. The project explicitly states it is highly experimental and not approved for therapy, positioning it as a research and community-driven initiative rather than a medical device cleared for clinical use.

The app provides comprehensive glucose monitoring and insulin delivery management through both iPhone and Apple Watch interfaces. On iPhone, users can view real-time glucose graphs, perform bolus calculations and insulin delivery, and receive notifications for critical events including loop failures and pump battery changes. The Apple Watch integration extends functionality to the wrist, allowing users to enter carbohydrate information, perform bolus actions, and receive notifications about reservoir levels and delivery failures. The interface includes status screens, bolus entry screens, and various alert notifications designed to keep users informed of their system status.

Loop is built on the work of many contributors and represents a collaborative effort in the open-source diabetes technology community. The project maintains documentation through Loop Docs at loopdocs.org, which covers installation procedures, algorithm details, and technical specifications. A wiki provides additional resources including FAQs and contribution guidelines for those interested in participating in the open-source aspects of the project.

The repository is classified across multiple diabetes and medical technology categories including insulin delivery, closed-loop systems, artificial pancreas technology, glucose monitoring, insulin pump integration, and health management on the iOS platform. This comprehensive classification reflects Loop's position as a sophisticated medical application addressing multiple aspects of automated diabetes care. The project's combination of technical sophistication, active community maintenance, and explicit disclaimers about its experimental status makes it a notable example of community-driven medical technology development.