Noninvasive Bioinformation Estimation Using Spectral and Metabolic Data Fusion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for monitoring blood glucose levels in diabetes patients are invasive, causing pain and infection risks, and there is a need for non-invasive techniques that can accurately estimate bio-information without blood sampling.
Innovation Solution
An apparatus comprising a spectrometer, sensors for metabolic and physiological information, and a processor that identifies a predictive model to estimate bio-information based on light absorbance and metabolic data, using combinations of reference spectra and physiological indicators like CO2 concentration, body temperature, heart rate, and pulse wave features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If an invasive method of finger pricking is used to measure blood glucose levels, then measurement reliability is improved, but pain and infection risk increase
Solution Approach 1:
The patent replaces the mechanical invasive finger pricking method with an optical measurement system using a spectrometer. The spectrometer measures light absorbance spectra from the user's tissue, and a processor analyzes these spectra along with metabolic information (CO2 concentration, body temperature, heart rate, pulse wave features) to estimate blood glucose levels non-invasively, thereby eliminating pain and infection risk while maintaining measurement reliability through multiple data fusion.
2Object-affected harmful factors
If a non-invasive method using spectrometer is used to estimate blood glucose, then pain and infection risk are reduced, but measurement accuracy may deteriorate
Solution Approach 1:
The patent combines multiple measurement modalities into a unified estimation system. The spectrometer measures light absorbance spectra, while separate sensors simultaneously measure CO2 concentration, body temperature, heart rate, and pulse wave features. The processor integrates all these diverse data sources using predictive models to estimate blood glucose levels, thereby compensating for the limitations of any single non-invasive measurement method and achieving high measurement accuracy.
Solution Approach 2:
The patent utilizes changes in multiple physiological parameters (light absorbance at different wavelengths, CO2 concentration, body temperature, heart rate, pulse wave characteristics) to estimate blood glucose levels. By monitoring how these parameters change in response to glucose level changes and using predictive models to correlate these changes, the system achieves accurate non-invasive glucose estimation without relying on a single parameter that may be insufficient alone.
3Measurement precision
If multiple sensors for metabolic and physiological information are added, then estimation accuracy is improved, but device complexity increases
Solution Approach 1:
The patent employs a multi-functional integrated system where a single processing unit handles data from multiple sensors (spectrometer, CO2 sensor, temperature sensor, heart rate sensor, pulse wave sensor). The processor executes predictive models that can process various combinations of metabolic and physiological information types, making the system adaptable and accurate while managing complexity through unified data processing architecture rather than separate dedicated systems for each measurement.
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 non-invasive estimation of bio-information such as blood glucose levels with high accuracy, reducing the risk of pain and infection, while providing a convenient and reliable method for diabetes management.
Implementation Method 1
a detector configured to detect the light scattered or reflected from the user
Implementation Method 2
a detector configured to detect the light scattered or reflected from the user
Implementation Method 3
configured to obtain a light absorbance spectrum from a user
Implementation Method 4
an optical gas sensor configured to obtain the CO2 concentration of the user
Implementation Method 5
a pulse wave sensor configured to obtain a pulse wave reflected from the user
Data Source
AI summary
Provided is an apparatus for estimating bio-information which estimates bio-information from a user. The apparatus for estimating bio-information according to an embodiment of the present disclosure includes: a spectrometer configured to obtain, absorbance from a user; a physiological information obtainer configured to obtain metabolic and physiological information including a concentration of carbon dioxide (CO2); and a processor configured to estimate bio-information based on the absorbance and the metabolic, and physiological information by using a predictive model corresponding to the obtained metabolic and physiological information.