Pulse Oximeter Wavelet Transform Respiration Extraction
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Solution Overview
Problem
Current pulse oximeter devices cannot directly measure respiration from photoplethysmogram (PPG) signals, requiring additional and obtrusive equipment, and lack robustness in oxygen saturation measurement correlation with actual blood oxygen levels.
Innovation Solution
The use of wavelet transform methods to extract clinically useful information from PPG signals, including respiration, pulse, and oxygen saturation, by employing wavelet feature extraction techniques such as Secondary Wavelet Feature Decoupling (SWFD) and wavelet-based Lissajous plots to derive accurate oxygen saturation values and monitor patient movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If additional equipment is used to measure respiration, then respiration measurement capability is improved, but device complexity and patient burden increase
Solution Approach 1:
The patent enables the pulse oximeter to perform multiple functions by extracting respiration information from the existing PPG signal alongside oxygen saturation measurement. The wavelet transform analysis extracts multiple frequency components from the PPG signal, allowing the single device to simultaneously measure SpO2, respiration rate, and detect movement artifacts without requiring additional sensors or equipment.
Solution Approach 2:
The patent uses wavelet transform as an intermediary mathematical tool to extract respiration information from the PPG signal. The wavelet transform acts as a mediator that decomposes the complex PPG signal into frequency components, allowing respiration rate extraction without direct respiratory sensing. This intermediary approach enables indirect measurement of respiration through signal processing rather than requiring additional physical sensors.
2Measurement precision
If traditional PPG analysis is used, then device simplicity is maintained, but measurement precision of oxygen saturation and respiration is insufficient
Solution Approach 1:
The patent changes the analysis parameters by applying wavelet transform with varying scales to the PPG signal. This mathematical transformation changes how the signal is viewed in the time-frequency domain, allowing extraction of multiple physiological parameters including SpO2 and respiration rate from the same signal. The parameter change approach improves measurement precision through better signal decomposition rather than adding more sensors.
Solution Approach 2:
The patent replaces direct mechanical/respiratory sensing with mathematical signal processing. Instead of using mechanical respiratory sensors or additional optical paths, the invention uses wavelet transform mathematics to extract respiration information from the existing PPG signal. This substitution of mechanical sensing with computational analysis maintains device simplicity while improving measurement precision.
3Adaptability or versatility
If PPG signal is used for multiple measurements, then device versatility is improved, but signal quality and measurement reliability deteriorate
Solution Approach 1:
The patent segments the PPG signal into different frequency components using wavelet transform. By decomposing the signal into distinct frequency bands corresponding to different physiological processes (heart rate, respiration, movement), the system can analyze each component separately. This segmentation allows reliable extraction of multiple parameters from a single PPG signal without the measurements interfering with each other, maintaining signal quality while improving versatility.
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 direct and robust measurement of respiration and oxygen saturation from PPG signals, improving the utility of pulse oximeters and reducing the need for additional equipment, while providing clinically useful information for patient monitoring.
Implementation Method 1
The wavelet transform of a signal x(t) is defined as where ψ*(t) is the complex conjugate of the wavelet function ψ(t), a is the dilation parameter of the wavelet and b is the location parameter of the wavelet.
Implementation Method 2
Oximetry is based on the ability of different forms of haemoglobin to absorb light of different wavelengths. Oxygenated haemoglobin (HbO2) absorbs light in the red spectrum and deoxygenated or reduced haemoglobin (RHb) absorbs light in the near-infrared spectrum.
Data Source
AI summary
A physiological measurement system is disclosed which can take a pulse oximetry signal such as a photoplethysmogram from a patient and then analyse the signal to measure physiological parameters including respiration, pulse, oxygen saturation and movement. The system can be used as a general monitor, or more specifically, to for infant or adult apnea, and to guard against sudden infant death syndrome. The system comprises a pulse oximeter which includes a light emitting device and a photodetector attachable to a subject to obtain a pulse oximetry signal; analogue to digital converter means arranged to convert said pulse oximetry signal into a digital pulse oximetry signal; signal processing means suitable to receive said digital pulse oximetry signal and arranged to decompose that signal by wavelet transform means; feature extraction means arranged to derive physiological information from the decomposed signal; an analyser component arranged to collect information from the feature extraction means; and data output means arranged in communication with the analyser component.