Noninvasive Blood Glucose Sensor Using NAS Spectral Correction
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Solution Overview
Problem
Current non-invasive methods for measuring blood glucose levels, such as optical sensors, face challenges in accuracy due to spectral changes unrelated to glucose concentration, leading to increased spectral residual and estimation errors.
Innovation Solution
A bio-signal analysis apparatus and method using a General Net Analyte Signal (NAS) algorithm that generates and updates a concentration estimation model based on in vivo spectra, identifying and correcting for spectral change factors unrelated to glucose concentration changes, thereby improving prediction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If non-invasive optical sensing is used to measure blood glucose, then patient comfort and safety are improved (no pain, infection risk, or inconvenience), but measurement accuracy deteriorates due to spectral changes unrelated to glucose concentration
Solution Approach 1:
The patent extracts and removes spectral change factors unrelated to glucose concentration from the measured spectrum. By identifying and eliminating these interfering factors (such as tissue scattering, hemoglobin absorption, and other physiological variations), the system isolates the glucose-specific spectral signature, thereby improving measurement accuracy while maintaining non-invasive operation
Solution Approach 2:
The patent introduces a spectral correction model as an intermediary between the raw optical measurement and the final glucose concentration calculation. This model acts as a mediator that compensates for spectral changes caused by physiological variations, tissue properties, and measurement conditions, enabling accurate glucose measurement without direct blood contact
2Measurement precision
If spectral correction models are updated frequently to maintain accuracy, then measurement precision is improved, but device complexity and computational requirements increase
Solution Approach 1:
The patent performs preliminary identification of spectral change factors during a calibration phase before actual glucose measurement. By pre-characterizing the spectral variations caused by different physiological conditions and storing correction parameters in advance, the system reduces real-time computational complexity while maintaining measurement accuracy
Solution Approach 2:
The patent implements periodic updates of the concentration estimation model at predetermined time intervals or under specific triggering conditions (such as significant physiological changes). This periodic update strategy balances accuracy maintenance with reduced computational burden compared to continuous updating
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method effectively reduces estimation errors and maintains accuracy over time by iteratively updating the concentration estimation model, reflecting real-time influences on spectral changes, thus enhancing the reliability of blood glucose prediction.
Implementation Method 1
a method of non-invasive measurement of blood glucose using an optical sensor
Data Source
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AI summary
An apparatus for estimating a concentration of an analyte may include a spectrum acquisition device configured to acquire a first in vivo spectrum of an object, and a processor configured to estimate the concentration of the analyte using the first in vivo spectrum and a concentration estimation model that is generated based on a second in vivo spectrum measured during a timeframe in which the concentration of the analyte in the object is substantially constant, and update the concentration estimation model based on the first in vivo spectrum and the estimated concentration of the analyte.