Insulin Delivery Pattern Analysis for Glucose Control
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Solution Overview
Problem
Current insulin delivery systems face challenges in processing and applying vast amounts of data from glucose monitoring, insulin delivery, and user behavior to improve user experience and physiological outcomes, such as blood glucose levels, due to data complexity and volume.
Innovation Solution
Systems and methods are developed to detect patterns, trends, anomalies, and abnormalities in insulin pump operation and user data, allowing for adjustments in insulin delivery timing and user behavior, such as exercise and eating patterns, to improve glucose levels, using a network of wearable devices and remote analysis to provide actionable insights and prompts for users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vast amounts of data from glucose monitoring, insulin delivery, and user behavior are collected, then user experience and physiological outcomes can be improved, but data processing complexity and system complexity increase
Solution Approach 1:
The system segments data processing into multiple components: glucose monitoring data processing, insulin delivery data processing, user behavior data processing, and pattern analysis processing. Each component handles specific data types independently before integration, reducing overall processing complexity while maintaining comprehensive analysis capability
Solution Approach 2:
The patent introduces an intermediary processing layer that collects raw data from multiple sources (glucose monitor, insulin pump, mobile device), processes and integrates this data, then presents actionable insights to users. This intermediary layer simplifies the complexity by abstracting detailed processing from end users while maintaining data-driven decision support
2Measurement precision
If continuous glucose monitoring and frequent data collection are implemented, then blood glucose control improves, but user burden and system complexity increase
Solution Approach 1:
The system implements self-service functionality by automatically collecting glucose data, insulin delivery data, and user behavior data without requiring manual entry. The system autonomously processes this data, identifies patterns, and generates recommendations, reducing user burden while maintaining continuous monitoring capability
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors glucose levels and automatically adjusts insulin delivery recommendations based on detected patterns. This closed-loop feedback reduces user burden by automating the control process while maintaining precise blood glucose management through continuous adjustment
Data Source
AI summary
Systems and methods are provided for determining patterns, trends, anomalies, and/or abnormalities in data relating to operation of an insulin delivery pump and user outcomes relating to an insulin delivery pump and determining certain actions and/or operational adjustments to improve the user outcomes, such as blood glucose levels. For example, troubleshooting actions may be recommended upon determining a pattern, trend, abnormality, and/or anomaly in blood glucose levels that is undesirable. In another example, operation of the insulin delivery pump may be adjusted based habits and/or behaviors of the user. For example, insulin delivery timing may be adjusted based on exercise, activity and/or eating patterns. Based on the detected patterns, trends, anomalies, and/or abnormalities, a user device such as a mobile phone or smart device may present prompts for more information, alerts, status updates, and other information intended to improve the user experience.