Autocorrelation Peak Filtering for PPG Respiration Rate Accuracy
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Solution Overview
Problem
Existing methods for determining respiration information from photoplethysmograph (PPG) signals are prone to inaccuracies due to noise, short-term breathing pattern variations, and measurement errors, leading to unreliable respiration rate calculations.
Innovation Solution
The method generates an autocorrelation sequence from the PPG signal, identifies a respiration peak, and creates a composite peak using previous respiration peaks to calculate respiration information, while checking for undesired harmonics to ensure accurate processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to determine respiration information from PPG signals, then the processing is simple, but the accuracy is low due to noise and measurement errors
Solution Approach 1:
The patent applies preliminary action by generating an autocorrelation sequence from the PPG signal before extracting respiration information. This preprocessing step identifies periodic patterns and potential respiration rates in advance, allowing the system to focus subsequent analysis on the most relevant frequency components, thereby improving accuracy while managing complexity.
Solution Approach 2:
The autocorrelation sequence serves as an intermediary between the raw PPG signal and the final respiration information. It transforms the complex physiological signal into a form where periodicity is more evident, making it easier to identify respiration rates and filter out noise and harmonics in the subsequent processing steps.
2Reliability
If only recent data is used for respiration calculation, then the processing is fast, but the reliability is low due to short-term breathing variations
Solution Approach 1:
The patent merges recent and historical respiration peak data into a composite peak representation. By combining information from multiple respiratory cycles and using autocorrelation to identify consistent periodic patterns across time, the system achieves more reliable respiration rate determination that is less sensitive to short-term breathing variations.
Solution Approach 2:
The system uses feedback by comparing identified respiration peaks with previously detected peaks and autocorrelation patterns. This iterative process allows the algorithm to refine its estimates of respiration rate, filtering out anomalies and confirming consistent patterns before finalizing the measurement, thereby improving reliability.
3Measurement precision
If autocorrelation sequence is analyzed without harmonic filtering, then the processing is simple, but the measurement precision is reduced due to undesired harmonics
Solution Approach 1:
The patent extracts and identifies undesired harmonics from the autocorrelation sequence by analyzing peak patterns and their relationships. Once identified, these harmonic components are separated or filtered out, allowing the system to focus on the fundamental respiration peak and improve the accuracy of respiration rate measurement.
Solution Approach 2:
The system changes parameters by examining the autocorrelation sequence at different lag values and analyzing the relationships between peaks. By varying the analysis parameters such as peak spacing ratios and amplitude relationships, the algorithm can distinguish between fundamental respiration peaks and harmonic components, improving identification accuracy.
Data Source
AI summary
Systems and methods are provided for determining respiration information from physiological signals such as PPG signals. A physiological signal is processed to generate at least one respiration information signal and an autocorrelation sequence is generated based on the at least one respiration information signal. In some embodiments, a respiration peak is identified based on the autocorrelation sequence and a composite peak is generated based on the identified peak and at least one previous respiration peak. Respiration information is calculated based on the composite peak. In some embodiments, a determination is made whether the autocorrelation sequence includes an undesired harmonic. When the autocorrelation sequence includes an undesired harmonic, the autocorrelation sequence may not be used in the calculation of respiration information.