Complex Number Encoding for Pulse Oximetry Signal Processing
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Solution Overview
Problem
Existing pulse oximetry methods face challenges in accurately calculating continuous and reliable blood oxygen saturation values due to issues with signal zero-crossing, low signal-to-noise ratio, and motion artifacts, leading to unreliable instantaneous saturation calculations.
Innovation Solution
The use of complex number encoding and Hilbert transform to generate complex photopleths, allowing for continuous and reliable calculations of the Red/Infrared AC ratio without concern for zero-crossing areas, and incorporating confidence measures to filter out unreliable data points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional pulse oximetry methods are used to calculate instantaneous saturation values, then the calculation process is simple, but the reliability of saturation values deteriorates due to zero-crossing issues and low signal-to-noise ratio
Solution Approach 1:
The patent introduces complex numbers as an intermediary representation to transform the real-valued photoplethysmograph signals into complex signals with magnitude and phase components. This intermediary transformation allows the system to avoid direct division operations that cause zero-crossing problems, thereby improving the reliability of saturation value calculations while managing computational complexity through structured complex arithmetic operations.
2Measurement precision
If traditional AC ratio calculation is performed, then computational simplicity is maintained, but measurement precision deteriorates due to motion artifacts and venous pulsation interference
Solution Approach 1:
The patent segments the photoplethysmograph signal into multiple frequency components using Fourier transform, separating the arterial pulse signal from venous pulsation and motion artifact interference. By analyzing specific frequency bands and combining results from multiple spectral components, the system achieves more precise saturation measurement while managing computational complexity through efficient frequency-domain processing.
3Loss of information
If signal filtering is applied to remove noise, then signal-to-noise ratio improves, but loss of information occurs due to attenuation of useful signal components
Solution Approach 1:
The patent performs preliminary normalization of the photoplethysmograph signals before further processing, adjusting the signal amplitudes to account for varying source intensities and bulk loss characteristics. This preliminary action preserves the relative information content of the signals while improving their quality for subsequent analysis, thereby reducing information loss while enhancing signal-to-noise ratio through preparatory signal conditioning.
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
This approach enables accurate, continuous monitoring of arterial saturation values over time, reducing errors and providing reliable saturation data even in noisy conditions, with improved diagnostic value and reduced impact from motion artifacts.
Implementation Method 1
As the photons propagate through the tissue, they are subjected to random absorption and scattering processes due to the nonhomogeneous nature of the tissue
Implementation Method 2
As the photons propagate through the tissue, they are subjected to random absorption and scattering processes due to the nonhomogeneous nature of the tissue
Data Source
AI summary
The disclosure includes pulse oximetry systems and methods for determining point-by-point saturation values by encoding photoplethysmographs in the complex domain and processing the complex signals. The systems filter motion artifacts and other noise using a variety of techniques, including statistical analysis such as correlation, or phase filtering.