AGP Intelligent Interpretation and Insulin Adjustment Method

ChangeBridge: Patent Apps - Health Informatics (G16H)

Detected March 26th, 2026

Summary

The USPTO has published a patent application from Northeastern University detailing an ambulatory glucose profile (AGP) intelligent interpretation and insulin adjustment method. This method utilizes an expert system to analyze patient data and provide decision support for basal and mealtime insulin adjustments.

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What changed

This document is a patent application (US20260088171A1) filed by Northeastern University with the USPTO. It describes an "AGP intelligent interpretation and insulin adjustment method based on expert system." The method involves establishing a knowledge base, constructing an expert system, creating a patient problem analysis tree, and developing rules for basal and mealtime insulin dosage adjustments using an interval type-2 fuzzy expert system.

This patent application does not impose any new regulatory obligations or compliance requirements on regulated entities. It represents a novel technological development in the field of diabetes management and health informatics. Compliance officers should note this as a technological advancement rather than a regulatory change impacting their operations.

Source document (simplified)

← USPTO Patent Applications

AMBULATORY GLUCOSE PROFILE (AGP) INTELLIGENT INTERPRETATION AND INSULIN ADJUSTMENT METHOD BASED ON EXPERT SYSTEM

Application US20260088171A1 Kind: A1 Mar 26, 2026

Assignee

Northeastern University

Inventors

Xia YU, Hongru LI, Xiaoyu SUN, Jian ZHOU, Jingyi LU, Xiaojing MA

Abstract

An ambulatory glucose profile (AGP) intelligent interpretation and insulin adjustment method based on an expert system includes: establishing a knowledge base in an inference mechanism; constructing an interpretation and decision support expert system with a simplified expert system architecture based on the knowledge base; constructing a patient problem analysis tree in three dimensions of hypoglycemia, blood glucose fluctuation, and hyperglycemia of patients; expanding each rule with expert AGP interpretation and empirical data; constructing a basal insulin dosage adjustment rule and a mealtime insulin dosage adjustment rule based on an interval type-2 fuzzy expert system; and adjusting a node of the patient problem analysis tree based on the interpretation and decision support expert system and a group of the patient, and providing a decision suggestion in combination with the basal insulin dosage adjustment rule and the mealtime insulin dosage adjustment rule.