Dynamic Biometric Sampling Rate Control for Glucose Monitoring
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Solution Overview
Problem
Existing continuous glucose monitoring systems (CGMS) face accuracy issues due to biological reactions at the initial stage of sensor insertion, leading to sensitivity changes and inaccurate glucose level measurements, especially during abnormal glucose levels or sensor malfunctions.
Innovation Solution
An apparatus and method for controlling biometric data by optimizing the sampling rate based on indicator values and threshold comparisons, adjusting the sampling rate dynamically to maintain accuracy and adapt to user-specific conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a continuous glucose monitoring system uses a fixed sampling rate, then the system structure is simple, but the measurement precision decreases during abnormal glucose levels or sensor malfunctions
Solution Approach 1:
The patent implements a dynamic sampling rate adjustment mechanism that automatically changes the sampling rate based on glucose level conditions. During normal glucose levels, a lower sampling rate is used to reduce power consumption and data processing load. When abnormal glucose levels are detected or sensor malfunction occurs, the system automatically increases the sampling rate to improve measurement precision and response speed, thus resolving the contradiction between measurement precision and device complexity
Solution Approach 2:
The system incorporates a feedback mechanism where the sampling rate is continuously adjusted based on real-time glucose level data and sensor status. The control unit monitors glucose readings and sensor performance, and dynamically modifies the sampling rate accordingly. This feedback-based adaptive control enables the system to maintain high measurement precision during critical events while keeping the overall system complexity manageable through automated decision-making algorithms
2Measurement precision
If the sampling rate is increased to detect abnormal glucose levels, then the measurement precision improves, but the power consumption increases
Solution Approach 1:
The patent employs dynamic sampling rate adjustment to optimize power consumption. During normal glucose levels, the system operates at a lower sampling rate, significantly reducing power consumption of the sensor transmitter. When abnormal glucose levels are detected, the sampling rate is temporarily increased to improve detection accuracy. This dynamic adaptation resolves the contradiction by matching power consumption to actual monitoring needs rather than maintaining a constantly high sampling rate
Solution Approach 2:
The system implements periodic sampling with variable intervals rather than continuous high-rate sampling. During stable glucose conditions, sampling occurs at extended intervals to conserve power. When abnormal conditions are detected, the sampling frequency is increased temporarily. This periodic action with adaptive intervals enables the system to achieve high measurement precision during critical events while maintaining low average power consumption throughout the monitoring period
Data Source
AI summary
A method of controlling biometric data includes: obtaining first biometric data collected according to a first sampling rate; acquiring at least one first indicator value related to a first time interval of the first biometric data; acquiring at least one second indicator value related to a preset second time interval of the first biometric data; obtaining a first comparison result based on a difference value between the at least one first indicator value and the at least one second indicator value and threshold values set related to the first indicator value and the second indicator value; obtaining a first adjustment result for the first sampling rate based on the first comparison result; and determining a first variable sampling rate for the first biometric data based on the first adjustment result.