PPG Glucose Analysis with Bias-Adjusted Curve Fitting
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Solution Overview
Problem
Conventional non-invasive methods for monitoring blood glucose concentration using wearable smart devices suffer from low accuracy due to interference from human tissue.
Innovation Solution
A method involving curve fitting on intensity sets derived from photoplethysmography pulse waves, adjusting fitting biases to match individual object differences, and incorporating correction parameters to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of stationary object
If conventional near-infrared non-invasive detection method is used, then continuous monitoring of blood glucose concentration is achieved, but measurement precision deteriorates due to interference from human tissue
Solution Approach 1:
The patent changes the detection parameters by using photoplethysmography pulse wave intensity characteristics (average alternating-current intensity and average direct-current intensity) instead of conventional near-infrared absorption. It also introduces curve fitting parameters (fitting coefficient and fitting bias) and correction parameters to transform the raw intensity data into accurate blood glucose concentration values, thereby improving measurement precision while maintaining continuous monitoring capability
Solution Approach 2:
The patent replaces the conventional near-infrared optical detection mechanism with a photoplethysmography-based intensity analysis mechanism. By substituting the detection approach from near-infrared absorption measurement to photoplethysmography pulse wave intensity measurement combined with curve fitting, it overcomes the tissue interference problem while achieving continuous blood glucose monitoring
2Measurement precision
If curve fitting with adjusted fitting bias is performed, then measurement precision improves by aligning with individual object characteristics, but device complexity increases due to additional processing steps
Solution Approach 1:
The patent implements self-service by automatically determining individual bias ranges through historical data and automatically adjusting the fitting bias within this range. The system performs self-calibration by using the wearer's own historical photoplethysmography data to establish personalized parameters, eliminating the need for manual calibration while improving measurement precision
Solution Approach 2:
The patent incorporates feedback mechanisms by comparing the adjusted fitting coefficient with reference values and iteratively optimizing the fitting parameters. The system uses historical data feedback to continuously refine the bias range and correction parameters, thereby improving accuracy while managing processing complexity through adaptive learning
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
Improves the accuracy of blood glucose concentration monitoring by aligning fitting coefficients with individual object characteristics, using adjusted fitting coefficients combined with correction parameters.
Implementation Method 1
acquiring intensity sets respectively corresponding to multiple photoplethysmography pulse wave sets for a target object in a target time period
Data Source
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AI summary
The present application relates to a method and apparatus for analyzing a blood glucose concentration, a device, a storage medium, and a computer program product. The method comprises: acquiring intensity sets corresponding to a plurality of photoplethysmography pulse wave sets for a target object in a target time period, the intensity set comprising an average alternating-current intensity and an average direct-current intensity; performing curve fitting on the plurality of intensity sets to obtain a fitting coefficient and a fitting bias; comparing the fitting bias with a bias range corresponding to the target object, and when it is determined that the fitting bias is not within the bias range, adjusting the fitting bias to obtain an adjusted fitting bias; and performing, on the basis of the adjusted fitting bias, curve fitting on the plurality of intensity sets to obtain an adjusted fitting coefficient, and taking the adjusted fitting coefficient as the blood glucose concentration of the target object in the target time period. By adopting the method, the accuracy of blood glucose concentration analysis can be improved.