Non-Invasive Analyte Accuracy via Synthetic Spectra
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Solution Overview
Problem
Existing methods for determining analyte concentration, especially non-invasive ones, face challenges in accurately calculating analyte concentrations without invasive procedures, requiring calibration models and invasive true values for validation.
Innovation Solution
An electronic device and method that non-invasively calculate analyte concentration using a calibration model, subtracting a spectrum specific to the analyte from an in-vivo spectrum, generating a test calibration model based on feature vectors, and determining accuracy by comparing test concentrations with reference values, employing techniques like PCA and deep learning for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If non-invasive spectroscopy is used to calculate analyte concentration, then invasive behavior is avoided, but accuracy verification requires invasive true values
Solution Approach 1:
The patent creates a virtual copy of the invasive measurement process by generating synthetic spectra with known analyte concentrations through spectral addition. This virtual reference data allows accuracy verification without actual invasive sampling, resolving the contradiction between non-invasive operation and reliability verification
Solution Approach 2:
The patent introduces synthetic spectra as an intermediary between the non-invasive measurement and accuracy verification. These synthetic spectra, generated by adding known analyte spectra to background spectra, serve as a mediator that enables accuracy assessment without requiring direct invasive measurement
2Productivity
If calibration models are used to calculate analyte concentration non-invasively, then measurement speed is improved, but accuracy depends on model calibration quality
Solution Approach 1:
The patent implements a feedback mechanism where the calibration model's predictions are tested against synthetic spectra with known concentrations. The accuracy metrics calculated from comparing predicted versus known values provide feedback on model performance, allowing for model improvement while maintaining fast non-invasive measurement capability
Solution Approach 2:
The patent performs preliminary calibration and accuracy testing using synthetic spectra before actual non-invasive measurements are deployed. This preliminary action ensures the calibration model is properly trained and validated, improving measurement precision while maintaining the speed advantage of non-invasive methods
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
Enables high accuracy in determining analyte concentration non-invasively by generating a test calibration model and comparing test concentrations with reference values, ensuring reliability without the need for invasive methods, as demonstrated by experiments with glucose concentration calculations.
Implementation Method 1
Spectroscopy such as absorption spectroscopy and Raman spectroscopy may be used for non-invasive methods. An in-vivo spectrum is obtained from measurements of absorption of spectrum by a test subject
Implementation Method 2
Spectroscopy such as absorption spectroscopy and Raman spectroscopy may be used for non-invasive methods. The in-vivo spectrum includes information on biomolecules included in the test subject
Data Source
AI summary
An electronic device determines accuracy of an analyte concentration non-invasively by calculating an analyte concentration of an analyte from an in-vivo spectrum obtained non-invasively using a calibration model, generates a test calibration model based on feature vectors of the in-vivo spectrum obtained non-invasively from which a spectrum specific to the analyte have been subtracted, calculates a test concentration for the analyte from the in-vivo spectrum using the test calibration model, and analyzes the test concentration for the analyte using the test calibration model to determine the accuracy of the analyte concentration using the calibration model.