PPG Signal Drift and Noise Correction via Wavelet Transform
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Solution Overview
Problem
Photoplethysmogram (PPG) signal measurements are affected by artifacts such as baseline drift, high frequency noise, and motion artifacts, which degrade the accuracy of physiological parameter measurements.
Innovation Solution
A method and system that removes baseline drift using discrete wavelet transform, filters the signal with a Butterworth filter to remove high frequency noise, and performs motion artifact correction using continuous wavelet transform to obtain a corrected PPG signal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If baseline drift removal is applied to PPG signal, then measurement accuracy is improved, but signal processing complexity increases
Solution Approach 1:
The patent applies discrete wavelet transform to segment the PPG signal into different frequency components, allowing selective removal of baseline drift while preserving physiological signal characteristics. This segmentation enables targeted processing that improves accuracy without requiring complete signal reconstruction.
Solution Approach 2:
The patent uses wavelet coefficients as an intermediary representation to facilitate drift removal. By transforming the signal into the wavelet domain, the baseline drift can be identified and removed through coefficient modification, then inverse transform is applied to obtain the corrected signal. This intermediary approach simplifies the overall processing complexity.
2Measurement precision
If high frequency noise filtering is applied to PPG signal, then measurement accuracy is improved, but signal processing complexity increases
Solution Approach 1:
The patent extracts high frequency noise components from the PPG signal using spectral analysis and wavelet transform. By identifying and separating the noise from the physiological signal in the frequency domain, the patent can remove only the harmful high frequency components while preserving the underlying signal integrity.
Solution Approach 2:
The patent changes the frequency parameters of the signal through wavelet transform, allowing selective filtering at different frequency bands. By adjusting the frequency parameters and wavelet coefficients, the system can effectively remove high frequency noise while maintaining the physiological characteristics of the PPG signal.
3Measurement precision
If motion artifact correction is applied to PPG signal, then measurement accuracy is improved, but signal processing complexity increases
Solution Approach 1:
The patent applies continuous wavelet transform to dynamically analyze the PPG signal in both time and frequency domains. This dynamic approach allows the system to identify and correct motion artifacts at their occurrence points, adapting to varying signal conditions without requiring complex predetermined correction models.
Solution Approach 2:
The patent uses wavelet coefficient analysis as feedback to identify motion artifacts and adjust correction parameters accordingly. By continuously monitoring the signal characteristics through wavelet transform and comparing them against expected physiological patterns, the system can adaptively correct motion artifacts while minimizing processing complexity.
Data Source
AI summary
The present disclosure relates to a method and system for processing a photoplethysmogram (PPG) signal to improve accuracy of measurement of physiological parameters of a subject. The method may include removing a baseline drift from the PPG signal; obtaining a drift removed signal; filtering the drift removed signal; obtaining a filtered signal; performing motion artifact correction on the filtered signal; and obtaining a corrected signal.