SYSTEMS AND METHODS FOR A DATA DRIVEN FRAMEWORK FOR ACTIONABLE FEEDBACK IN INSULIN MANAGEMENT FOR TYPE 1 DIABETIC SUBJECTS ON ARTIFICIAL PANCREAS

摘要

The present disclosure discloses a data science driven system and associated methodology framework for mining relevant knowledge from input/output traces of a closed-loop control system for glycemic control to aid in actionable feedback for Type 1 diabetes management. The framework takes Continuous Glucose Monitor (CGM) records and insulin pump records from a closed loop control (CLC) system and interprets the CGM records and insulin pump data to provide medically useful information, wherein the closed-loop control system is operable for operation in an "auto mode" (AP) and a "manual mode" (SAP).