Oxygen Saturation Calculation Using Wavelet Spectral Analysis
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Solution Overview
Problem
Current methods for determining oxygen saturation from photoplethysmographic signals face challenges in accuracy and noise resilience, particularly in tracking changes in pulse rate and ignoring temporally discrete artifacts.
Innovation Solution
The use of continuous wavelet transforms in conjunction with spectral transforms to calculate oxygen saturation, where the CWT focuses on frequency regions identified by spectral techniques, providing enhanced resolution in the time domain and improved noise resistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If spectral averaging techniques are used to calculate oxygen saturation, then the calculation is computationally efficient, but the ability to track changes in pulse rate and resolve temporal features is degraded
Solution Approach 1:
The patent segments the signal analysis into two distinct approaches: spectral analysis for identifying frequency regions of interest, and wavelet analysis for precise temporal tracking. This segmentation allows each method to be applied where it is most effective, resolving the contradiction between computational efficiency and measurement precision.
Solution Approach 2:
The patent transitions from purely spectral analysis (frequency domain) to wavelet analysis (time-frequency domain), adding the temporal dimension to the analysis. This dimensional change enables simultaneous tracking of both pulse rate changes and oxygen saturation while maintaining computational feasibility through selective application.
2Measurement precision
If continuous wavelet transforms are used to track pulse rate changes, then temporal resolution is improved, but computational complexity increases
Solution Approach 1:
The patent performs preliminary spectral analysis to identify frequency regions of interest before applying the computationally intensive wavelet transform. This preliminary action reduces the scope of subsequent wavelet analysis to only relevant frequency bands, thereby reducing overall computational complexity while maintaining temporal resolution benefits.
Solution Approach 2:
The patent applies wavelet analysis selectively to specific frequency regions identified as containing pulse rate information, rather than analyzing the entire spectrum. This localized application maintains high temporal resolution where needed while reducing computational complexity in regions where spectral averaging suffices.
3Productivity
If spectral transforms are used to identify frequency components, then the identification of pulse rate regions is efficient, but the ability to ignore temporally discrete artifacts is reduced
Solution Approach 1:
The patent uses spectral analysis as an intermediary step to identify frequency regions of interest, which then guides the wavelet analysis. This intermediary approach allows efficient frequency identification while the subsequent wavelet analysis acts as a filter to eliminate temporally discrete artifacts, combining the strengths of both methods.
Solution Approach 2:
The patent employs feedback by using the results of spectral analysis to inform and constrain the wavelet analysis parameters. The frequency regions identified by spectral transforms provide feedback that directs the wavelet transform to focus computational resources on relevant time-frequency regions, improving artifact rejection while maintaining efficiency.
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 results in a more accurate and efficient calculation of oxygen saturation, effectively tracking changes in pulse rate and reducing the impact of noise, leading to improved reliability in oxygen saturation measurements.
Implementation Method 1
using continuous wavelet transforms and spectral transforms to determine oxygen saturation from a photoplethysmographic (PPG) signal
Data Source
AI summary
According to embodiments, techniques for using continuous wavelet transforms and spectral transforms to determine oxygen saturation from photoplethysmographic (PPG) signals are disclosed. According to embodiments, a first and a second PPG signals may be received. A spectral transform of the first and the second PPG signals may be performed to produce a first and a second spectral transformed signals. A frequency region associated with a pulse rate of the PPG signals may be identified from the first and the second spectral transformed signals. According to embodiments, a continuous wavelet transform of the first and the second PPG signals may be performed at a scale corresponding to the identified frequency region to produce a first and a second wavelet transformed signals. The oxygen saturation may be determined based at least in part upon the wavelet transformed signals.