Integrated Glucose Alarm Control Using Insulin Delivery Data
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Solution Overview
Problem
Existing glucose monitoring systems generate unreliable projected alarms due to limited data availability, leading to false alarms and misdetections, and lack integration with insulin delivery systems for real-time management.
Innovation Solution
An integrated glucose monitoring system that processes glucose level measurements with exogenous data such as insulin on board, insulin sensitivity, and carbohydrate intake to provide more reliable projected alarms and adjust insulin delivery parameters in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If glucose monitoring systems use only monitored glucose data to generate projected alarms, then the system simplicity is maintained, but the reliability of projected alarms deteriorates due to false alarms and misdetections
Solution Approach 1:
The patent combines continuous glucose monitoring (CGM) data with continuous insulin delivery (CID) data into an integrated system. The processor accesses both glucose level data and insulin delivery data to generate projected alarms, merging previously separate monitoring and delivery functions into a unified system that improves alarm reliability through comprehensive data analysis.
Solution Approach 2:
The integrated processor acts as an intermediary that receives and processes data from both the CGM sensor and the insulin delivery pump. It combines these data streams, applies predictive algorithms considering both glucose trends and insulin on board, and generates coordinated alarm signals and control recommendations, serving as a mediator between monitoring and delivery subsystems.
2Productivity
If glucose monitoring and insulin delivery are accomplished by different hardware devices, then device simplicity and ease of manufacture are maintained, but the effectiveness of real-time management deteriorates due to lack of data sharing
Solution Approach 1:
The patent merges separate glucose monitoring and insulin delivery hardware devices into an integrated system. The unified device includes both a CGM sensor for continuous glucose measurement and a CID pump for continuous insulin delivery, with a shared processor that accesses data from both functions to enable coordinated real-time management and improve therapeutic effectiveness.
Solution Approach 2:
The integrated device performs multiple functions within a single system: continuous glucose monitoring, continuous insulin delivery, data processing, alarm generation, and control recommendations. This multi-functional approach eliminates the need for separate devices while enhancing real-time management capabilities through shared resources and coordinated operation.
3Measurement precision
If projected alarms are generated without incorporating exogenous data such as insulin on board and carbohydrate intake, then the ease of operation is maintained, but the accuracy of glucose level predictions deteriorates
Solution Approach 1:
The integrated system automatically collects and processes exogenous data (insulin delivery amounts, carbohydrate intake information) without requiring manual input from the user. The processor autonomously accesses this data from the system's memory and uses it in predictive algorithms, maintaining ease of operation while significantly improving prediction accuracy through comprehensive data utilization.
Data Source
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AI summary
Continuous glucose monitoring (CGM) data and insulin delivery data are used to generate more reliable projected alarms related to a projected glucose levels. A memory stores endogenous data related to measurements of glucose level in a patient, and also stores exogenous data, such as insulin on board, both of which are used by a processor to create projected alarms. Profiles of CGM data are created for use in tuning patient-specific insulin data, such at basal rate, carb ratio, and insulin sensitivity. A processor searches for patterns in the data profiles and if found, recommended changes to patient-specific insulin data are provided to permit more accurate control over a patient's glucose levels.