Tissue Oximetry Reflectance Curve Fitting for Pulse-Free Saturation
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Solution Overview
Problem
Existing oximeters face challenges in improving measurement accuracy, reducing measurement time, lowering cost, and reducing size and power consumption, particularly in non-ideal conditions, and there is a need for accurate oxygen saturation measurements in clinical settings like surgery where tissue viability is critical.
Innovation Solution
A tissue oximetry device uses a large number of simulated reflectance curves to determine optical properties, including emitting light, detecting reflections, and fitting data points to stored curves to calculate oxygen saturation, allowing for accurate measurements without requiring a pulse.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If existing oximeters use traditional measurement methods, then measurement accuracy is maintained, but measurement time is prolonged and device complexity increases
Solution Approach 1:
The system pre-calculates and stores a comprehensive library of simulated reflectance curves covering a wide range of tissue optical properties before actual measurement. This preliminary preparation allows the device to quickly search through pre-computed data during measurement rather than performing complex real-time calculations, thereby reducing measurement time while maintaining accuracy through the use of extensive pre-simulated data
Solution Approach 2:
The system creates a digital copy of tissue optical behavior through simulated reflectance curves that model how light interacts with tissue at different oxygen saturation levels. By using these simulated curves as references for comparison against actual measurements, the device can rapidly determine oxygen saturation without requiring complex real-time physical measurements, thus reducing measurement time while preserving measurement precision
2Measurement precision
If a large number of simulated reflectance curves are used, then measurement accuracy is improved, but device complexity and memory requirements increase
Solution Approach 1:
The system uses simulated reflectance curves that are pre-calculated and stored in memory, creating a digital reference library that captures the optical behavior of tissue across various conditions. This approach replaces complex real-time computational models with pre-computed data copies, allowing the device to maintain high measurement accuracy through extensive curve libraries while keeping the actual measurement process simple and the device architecture manageable
Solution Approach 2:
The comprehensive library of simulated reflectance curves is generated and stored in advance during device manufacturing or initialization. This preliminary computation phase separates the complex computational work from the actual measurement process, allowing the device to use simple comparison algorithms during measurement while still benefiting from the accuracy of extensive pre-simulated data, thus reducing operational device complexity
3Adaptability or versatility
If traditional oximetry methods are used, then device simplicity is maintained, but adaptability to non-ideal conditions deteriorates
Solution Approach 1:
The simulated reflectance curve library is designed to cover a broad range of tissue types, optical properties, and measurement conditions. By incorporating curves that represent various tissue compositions, scattering properties, and anatomical locations, the system becomes universally applicable across different clinical scenarios and non-ideal conditions, maintaining measurement accuracy where traditional methods would fail
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
The device provides rapid and precise oxygen saturation measurements in various conditions, including tissues without a pulse, enhancing clinical applications such as surgery and plastic surgery.
Implementation Method 1
emitting light from a set of light sources into tissue; detecting the light by a plurality of detectors subsequent to reflection of the light from the tissue
Implementation Method 2
Light absorption differs significantly for oxygenated and deoxygenated hemoglobins at certain wavelengths of light. Tissue oximeters can measure oxygen levels in human tissue by exploiting these light-absorption differences
Data Source
AI summary
A method for determining oxygen saturation includes emitting light from sources into tissue; detecting the light by detectors subsequent to reflection; and generating reflectance data based on detecting the light. The method includes determining a first subset of simulated reflectance curves from a set of simulated reflectance curves stored in a tissue oximetry device for a coarse grid; and fitting the reflectance data points to the first subset of simulated reflectance curves to determine a closest fitting one of the simulated reflectance curves. The method includes determining a second subset of simulated reflectance curves for a fine grid based on the closest fitting one of the simulated reflectance curves; determining a peak of absorption and reflection coefficients from the fine grid; and determining an absorption and a reflectance coefficient for the reflectance data points by performing a weighted average of the absorption coefficients and reflection coefficients from the peak.