Optical Blood Analyte Estimation Using Interval-Specific Models
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Solution Overview
Problem
Current methods for measuring blood triglyceride levels are invasive, causing pain and risk of infection, and lack noninvasive alternatives that can accurately track changes over time.
Innovation Solution
An apparatus and method using an optical sensor to emit light on the skin, detect optical signals, and select an interval-specific blood concentration estimation model based on physiological and optical properties to estimate analyte concentrations, such as triglycerides, without direct blood collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If an invasive method of collecting and analyzing blood is used, then measurement reliability is improved, but user comfort deteriorates due to pain and infection risk
Solution Approach 1:
The patent replaces the mechanical invasive blood collection system with an optical measurement system. The optical sensor emits light through the skin to detect analyte concentrations noninvasively, eliminating needles and blood draws while maintaining measurement capability through optical absorption and scattering properties of blood components
Solution Approach 2:
The patent introduces optical properties (absorption coefficient, scattering coefficient) as intermediary parameters that correlate with blood analyte concentrations. These optical intermediaries are measured noninvasively and then mapped to analyte levels through machine learning models, serving as a bridge between noninvasive measurement and blood concentration information
2Device complexity
If a single blood concentration estimation model is used, then device complexity is reduced, but measurement precision deteriorates across different physiological conditions
Solution Approach 1:
The patent segments the blood concentration estimation into multiple interval-specific models, each optimized for different physiological conditions or analyte concentration ranges. The system divides the estimation task into separate models that handle different intervals of optical properties or blood concentration ranges, improving overall accuracy across diverse conditions
Solution Approach 2:
The patent implements dynamic model selection where the appropriate estimation model is automatically chosen based on real-time optical property measurements and user characteristics. The system adapts to different physiological states by selecting the most suitable model from the plurality of interval-specific models, maintaining high precision across changing conditions
3Measurement precision
If multiple interval-specific blood concentration estimation models are used, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-training multiple interval-specific estimation models during the device setup or manufacturing phase. User-specific parameters such as skin properties, body composition, and baseline optical characteristics are measured in advance to configure the appropriate models, so that during actual measurement only model selection and simple computation are needed
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors optical property measurements and compares them against predictions from multiple interval-specific models. The feedback loop selects the model with the best fit for current conditions and uses it for estimation, automatically managing model complexity without user intervention
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 noninvasive, accurate estimation of blood analyte concentrations, including triglycerides, by using optical signals and machine learning models, reducing pain and infection risks while providing a reliable health indicator for fat intake and metabolism.
Implementation Method 1
an optical sensor configured to emit light towards a skin surface of a user, and detect an optical signal reflected by the skin surface of the user
Implementation Method 2
The optical property may be a scattering coefficient or an effective attenuation coefficient
Data Source
AI summary
An apparatus for estimating blood concentration may include an optical sensor configured to emit light towards a skin surface of a user, and detect an optical signal reflected by the skin surface of the user, and a processor configured to select an interval-specific blood concentration estimation model, from among a plurality of interval-specific blood concentration estimation models, based on an interval selection indicator and estimate a blood concentration change or a blood concentration of an analyte using the selected interval-specific blood concentration estimation model and the detected optical signal.