Multi-Band Physiological Sensing for Interference-Corrected Glucose
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Solution Overview
Problem
Current non-invasive blood glucose testing technologies suffer from low accuracy due to poor optical performance, individual differences among testees, and interference from various physiological values in the body.
Innovation Solution
A physiological value sensing device utilizing a multi-band light source and computing module to generate optical signals, create a physiological normal model, and employ an artificial intelligence model to fit and eliminate interference signals, thereby estimating physiological values accurately.
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 needle puncture), but measurement precision deteriorates due to interference from other physiological substances
Solution Approach 1:
The patent segments the optical spectrum into multiple wavelength bands (e.g., 800-1700nm with intervals of at least 100nm) to separately detect different physiological substances. By dividing the measurement into spectral segments, the system can distinguish glucose signals from interference substances like water, fats, and proteins through their unique absorption characteristics at different wavelengths.
Solution Approach 2:
The patent changes the optical parameter (wavelength) to improve measurement precision. By using multi-band light with specific wavelength ranges and adjusting light intensity, the system can selectively detect glucose while minimizing interference from other substances. The computing module processes these parameter variations to extract accurate glucose measurements.
2Device complexity
If conventional single-band optical sensing is used, then device complexity is reduced, but measurement precision deteriorates due to inability to eliminate interference signals
Solution Approach 1:
The patent adds a spectral dimension to the optical sensing system by implementing multi-band light detection. Instead of using a single wavelength, the system measures optical signals across multiple wavelength bands, creating a spectral fingerprint for each physiological substance. This dimensional expansion enables the computing module to differentiate between glucose and interference substances through pattern recognition.
3Measurement precision
If multi-band light with narrow wavelength interval is used, then measurement precision is improved through better spectral resolution, but device complexity and energy consumption increase
Solution Approach 1:
The patent applies partial action by selecting specific wavelength bands (800-1700nm with intervals of at least 100nm) that are most effective for detecting glucose and distinguishing it from interference substances. Rather than continuously scanning all possible wavelengths, the system focuses on discrete, optimized bands that provide sufficient spectral resolution for accurate measurement while minimizing energy consumption.
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
Enhances sensing accuracy by correcting interference from substances like water, fats, and proteins, providing real-time, continuous, and long-term monitoring of blood glucose levels.
Implementation Method 1
the at least one light detection unit is used to receive a reflection light reflected by the multi-band light illuminating the testee
Implementation Method 2
the light emitting units are capable of providing the multi-band light with a wavelength of 800 nanometers to 1700 nanometers and a wavelength interval of not less than 100 nanometers
Data Source
AI summary
A physiological value sensing device and a sensing method thereof are provided. The physiological value sensing device comprises an input module and a computing module. The input module is used to provide a multi-band light to illuminate a testee to generate a plurality of optical signals, and the optical signals include a plurality of interference signals and a physiological target signal. The computing module is used to establish a physiological normal model. The physiological normal model has multiple physiological sample values corresponding to the multi-band light. The computing module converts the interference signals and the physiological target signal into the physiological normal model for fitting. A physiological target value corresponding to the physiological target signal is generated after eliminating the interference signals based on the physiological sample values.