Pulse Processing Using Continuous Wavelet Transforms
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current pulse oximetry technologies face challenges in accurately processing photoplethysmographic (PPG) signals to determine physiological parameters like blood oxygen saturation and pulse rate, particularly due to noise and complexity in the signals, which affects the reliability of derived measurements.
Innovation Solution
The use of continuous wavelet transforms (CWT) to analyze PPG signals, allowing for high-resolution identification and characterization of pulse features, such as localized high energy regions and ridges, which enables the extraction of pulse information and simplification of the signal for easier processing of parameters like continuous non-invasive blood pressure and Heart Rate Variability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional pulse processing methods are used, then the processing is simpler, but the accuracy and reliability of pulse feature identification deteriorates due to noise and signal complexity
Solution Approach 1:
The patent segments the PPG signal into individual pulse waves using peak detection algorithms. Each pulse is isolated and analyzed separately, allowing for precise feature identification while managing complexity through systematic processing of discrete units rather than continuous complex signals
Solution Approach 2:
The patent introduces an intermediary processing stage that calculates multiple parameters (peak time, peak amplitude, area under curve, rise time, decay time) for each detected pulse. These intermediate parameters serve as mediators that transform the raw complex signal into structured data that is easier to analyze and less susceptible to noise interference
2Reliability
If continuous wavelet transforms are used to filter noise and identify features, then the reliability of measurements improves, but the processing time and computational complexity increase
Solution Approach 1:
The patent performs preliminary peak detection and pulse segmentation before conducting detailed waveform analysis. By identifying pulse boundaries and characteristic points first, the system prepares the signal in advance, reducing the computational burden of subsequent analysis and enabling faster processing while maintaining high reliability
Solution Approach 2:
The patent calculates multiple parameters for each pulse (peak time, peak amplitude, area under curve, rise time, decay time, systolic and diastolic times). This excessive calculation of parameters ensures comprehensive characterization of pulse features, improving measurement reliability while the systematic approach keeps processing manageable
3Measurement precision
If detailed waveform analysis is performed to extract physiological parameters, then the precision of parameter determination improves, but the complexity of processing increases
Solution Approach 1:
The patent applies different analysis methods to different portions of the pulse waveform. Characteristic points (peak, dicrotic notch, inflection points) are identified and analyzed with specific algorithms tailored to their local characteristics. This localized approach enables precise parameter extraction while avoiding the need for complex global analysis of the entire waveform
Data Source
AI summary
According to embodiments, techniques for using continuous wavelet transforms to process pulses from a photoplethysmographic (PPG) signal are disclosed. The continuous wavelet transform of the PPG signal may be used to identify and characterize features and their periodicities within a signal. Regions, phases and amplitudes within the scalogram associated with these features may then be analyzed to identify, locate, and characterize a true pulse within the PPG signal. Having characterized and located the pulse in the PPG (possibly also using information gained from conventional pulse processing techniques such as, for example, by identifying turning points for candidate pulse maxima and minima on the PPG, frequency peak picking for candidate scales of pulses, etc.), the PPG may be parameterized for ease of future processing.