Infusion Device Calibration Factor Adjustment for Sensor Lag
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Solution Overview
Problem
Infusion pump systems face challenges in maintaining accuracy and reliability due to filtering-induced lag and transient changes in sensor output, which affect the calibration of insulin delivery in diabetic patients, leading to a degradation of user experience.
Innovation Solution
An infusion system that determines an adjusted calibration factor based on a raw calibration factor calculated from reference measurements and an expected calibration factor, influencing the operation of the infusion device to improve accuracy and reduce lag.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor data is filtered to reduce noise and improve accuracy, then measurement precision is improved, but filtering introduces lag that degrades user experience
Solution Approach 1:
The system dynamically adjusts the calibration factor based on transient state detection. When the sensor is determined to be in a transient state (exhibiting filtering-induced lag), the system automatically adjusts the calibration factor to compensate for the lag effect, thereby maintaining accurate glucose readings without requiring longer filtering periods.
Solution Approach 2:
The system changes the calibration parameter (calibration factor) based on the operating conditions. By detecting transient states and adjusting the calibration factor accordingly, the system adapts the measurement parameters to compensate for filtering-induced lag, resolving the contradiction between filtering accuracy and response time.
2Measurement precision
If calibration is performed using reference measurements, then accuracy is improved, but transient changes in sensor output can influence calibration accuracy and degrade reliability
Solution Approach 1:
The system performs preliminary detection of transient states before performing calibration. By identifying when the sensor is in a transient state, the system can prevent calibration during these periods or apply corrective adjustments, ensuring that calibration is only performed when the sensor output is stable and reliable.
Solution Approach 2:
The system implements feedback by continuously monitoring sensor output for transient states and adjusting the calibration factor accordingly. This closed-loop approach ensures that calibration accuracy is maintained by detecting and compensating for transient changes that would otherwise degrade calibration reliability.
3Reliability
If filtering is applied to reduce noise, then measurement reliability is improved, but filtering introduces lag that extends the time to obtain accurate readings
Solution Approach 1:
The system changes the calibration parameter dynamically based on filtering state. When filtering-induced lag is detected, the calibration factor is adjusted to compensate for the time delay, allowing the system to maintain high measurement reliability while reducing the effective time lag in obtaining accurate readings.
Data Source
AI summary
Infusion systems, infusion devices, and related operating methods are provided. An exemplary method of operating an infusion device capable of delivering fluid to a user involves obtaining one or more uncalibrated measurements indicative of the physiological condition, obtaining one or more reference measurements of the physiological condition, determining a raw calibration factor based on a relationship between the one or more uncalibrated measurements and the one or more reference measurements corresponding to the respective uncalibrated measurements of the one or more uncalibrated measurements, and determining an adjusted calibration factor based at least in part on an expected calibration factor and the raw calibration factor, wherein operation of the infusion device to deliver the fluid is influenced by the adjusted calibration factor.