Glucose Sensor Signal Artifact Detection and Filtering
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Solution Overview
Problem
Conventional glucose sensors face challenges in accurately detecting and reporting continuous blood glucose levels due to noise from electronic and diffusion-related system noise, leading to inaccurate data streams and delayed detection of hyperglycemic or hypoglycemic conditions in diabetic patients.
Innovation Solution
A method and system for detecting and processing signal artifacts in glucose sensor data, which involves comparing received data with filtered data to determine residuals and thresholds, allowing for the identification and filtering of noise episodes caused by non-glucose reaction rate-limiting phenomena, thereby providing accurate glucose measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If conventional glucose sensors are used to continuously detect blood glucose levels, then continuous monitoring capability is provided, but measurement precision deteriorates due to electronic and diffusion-related system noise
Solution Approach 1:
The patent extracts and removes signal artifacts (noise episodes) from the glucose sensor data stream by comparing received data with filtered data to identify residuals that exceed thresholds, thereby separating the useful glucose signal from electronic and diffusion-related system noise
Solution Approach 2:
The patent introduces an intermediary processing system that acts as a mediator between the noisy sensor output and the final glucose measurement, using filtered data comparison and residual analysis to bridge the gap and produce accurate glucose readings despite the presence of system noise
2Measurement precision
If signal filtering is applied to remove noise from glucose sensor data, then measurement precision is improved, but loss of information occurs due to potential removal of valid signal components
Solution Approach 1:
The patent applies partial filtering by comparing received data with filtered data and only replacing values when residuals exceed specific thresholds, thereby applying filtering action selectively rather than universally to preserve valid signal components while removing noise
Solution Approach 2:
The patent uses feedback mechanisms where filtered data is compared with received data, and the comparison results (residuals) feed back into the decision-making process to determine whether to replace individual data points, allowing dynamic adjustment of filtering intensity based on actual signal conditions
3Reliability
If threshold-based artifact detection is used to identify noise episodes, then reliability of glucose data is improved, but device complexity increases due to additional processing requirements
Solution Approach 1:
The patent segments the data processing task into distinct stages: receiving raw data, applying filtering to generate filtered data, comparing received data with filtered data to calculate residuals, and evaluating residuals against thresholds to detect artifacts, thereby breaking down the complex processing into manageable segments
Data Source
AI summary
Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as interfering species, ischemia, pH changes, temperatures changes, known or unknown sources of mechanical, electrical and/or biochemical noise, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system processes some or the entire data stream continually or intermittently based at least in part on whether the signal artifact event has occurred.