Personalized Blood Glucose Correction Using Time Delay and Sensitivity Data
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Solution Overview
Problem
Continuous glucose monitoring (CGM) systems using interstitial sensors face inaccuracies due to patient-specific time delays and sensor-specific offsets, leading to delayed warning signals and poorer performance metrics like Absolute Relative Difference (ARD) when compared to capillary blood glucose measurements.
Innovation Solution
A method and system for determining blood glucose levels by detecting present sensor signals in continuous interstitial measurements, applying patient-specific signal corrections including time delay, sensor offset, and sensitivity data to improve accuracy, using data from former measurements to personalize corrections and reduce inaccuracy caused by mean correction values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If mean time lag correction is applied to interstitial glucose measurements, then the correction process is simplified, but measurement precision deteriorates due to patient-specific variations
Solution Approach 1:
The correction process is segmented into two levels: a general mean time lag correction applied to all patients, and an additional patient-specific time lag correction derived from historical data. This segmentation allows the system to maintain simplicity while improving precision for individual patients by adding only the necessary personalized adjustment.
Solution Approach 2:
The system performs preliminary analysis of historical interstitial glucose measurements and capillary blood glucose values to pre-calculate patient-specific time lag characteristics. This preliminary action enables the system to store and apply personalized correction factors in real-time measurements, improving accuracy without adding complexity during actual glucose monitoring.
2Measurement precision
If patient-specific correction data from former measurements is stored and applied, then measurement precision improves, but device complexity increases
Solution Approach 1:
Instead of implementing a completely new complex correction system for all patients, the invention applies local quality by maintaining the simple mean correction approach for the general population while providing enhanced patient-specific corrections only to those who have sufficient historical data available, thereby improving precision selectively without universally increasing system complexity.
Solution Approach 2:
The system utilizes already-collected historical measurement data from routine monitoring to automatically generate and apply patient-specific correction factors. This self-service approach allows the system to improve its own precision using existing resources without requiring additional external data collection or complex external processing systems.
3Productivity
If interstitial glucose measurement is used for continuous monitoring, then productivity of glucose monitoring is improved, but measurement precision deteriorates due to time lag
Solution Approach 1:
The system implements feedback by continuously comparing interstitial glucose measurements with reference capillary blood glucose values and using the differences to refine patient-specific time lag corrections. This feedback mechanism allows the system to maintain continuous monitoring productivity while progressively improving measurement precision through learned adjustments based on actual performance data.
Data Source
AI summary
The present disclosure refers to a method for determining a blood glucose level for a patient, the method comprising detecting a present sensor signal in a present continuous interstitial blood glucose measurement for a patient; providing measurement data representing the present sensor signal; providing sensor signal correction data representing a patient-specific signal correction, the sensor signal correction data being determined from a former interstitial blood glucose measurement for the patient and comprising at least one of time delay data representing a patient-specific time delay Δt between a blood glucose value measured in a continuous interstitial blood glucose measurement and a blood glucose reference value measured in a capillary blood glucose measurement, and sensor sensitivity data representing, for the patient, a patient-specific sensor sensitivity for the sensor, determining corrected measurement data representing a corrected present sensor signal by applying the sensor signal correction data to the present sensor signal; and determining a blood glucose level for the patient from the corrected measurement data.