Physiological Signal Processing Using Search and Locked Modes
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Solution Overview
Problem
Existing physiological monitoring systems face challenges in accurately determining pulse rate from photoplethysmographic signals due to noise components, subject movement, and variations in pulse shape, particularly in subjects with low perfusion or neonates, which can lead to incorrect rate determination.
Innovation Solution
A physiological monitor employing a processing module that utilizes search and locked modes with a narrow, adjustable band-pass filter, along with techniques such as autocorrelation, threshold analysis, and phase modulation, to qualify and determine physiological parameters like pulse rate by distinguishing between noise and physiological signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a narrow band-pass filter is used to improve noise rejection, then measurement precision is improved, but the filter may be initially tuned to noise or deviate from the correct physiological rate, reducing reliability
Solution Approach 1:
The system performs preliminary actions by using a search mode before locked mode to initialize the band-pass filter center frequency based on autocorrelation analysis of the PPG signal. This preliminary tuning ensures the filter is correctly positioned before narrow-band filtering is applied, preventing initial misalignment with noise or incorrect rates.
Solution Approach 2:
The system implements continuous feedback through qualification techniques that monitor the filtered signal quality and autocorrelation peaks. If the filter deviates from the correct physiological rate or locks onto noise, the feedback mechanism detects this through qualification failure and triggers a return to search mode to reset and re-tune the filter, maintaining reliable operation.
2Measurement precision
If signal processing techniques are applied to reject noise, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The processing system is segmented into distinct operational modes (search mode and locked mode) with specialized functions. The search mode handles initialization and rough tuning using autocorrelation, while locked mode performs precise filtering and monitoring. This segmentation allows each module to be optimized independently, managing overall system complexity.
Solution Approach 2:
The system employs self-service mechanisms where the qualification techniques automatically assess signal quality and trigger mode transitions without external intervention. The band-pass filter self-adjusts through the feedback loop, returning to search mode when qualification fails, reducing the need for complex external control mechanisms.
3Measurement precision
If autocorrelation and threshold analysis are used to determine pulse rate, then measurement precision is improved, but loss of time occurs due to extensive signal processing
Solution Approach 1:
The system performs preliminary autocorrelation analysis in search mode to quickly identify the approximate pulse rate and initialize the band-pass filter center frequency before transitioning to locked mode. This preliminary action reduces the processing burden in the subsequent precise measurement phase, optimizing the balance between accuracy and speed.
Solution Approach 2:
The system uses periodic action by implementing continuous qualification monitoring at defined intervals during locked mode operation. Rather than continuously re-processing the entire signal, the system periodically checks signal quality metrics and autocorrelation characteristics, maintaining precision while reducing overall processing time through structured periodic analysis.
Data Source
AI summary
A physiological monitoring system may process a physiological signal such a photoplethysmograph signal from a subject. The system may determine physiological information, such as a physiological rate, from the physiological signal. The system may use search techniques and qualification techniques to determine one or more initialization parameters. The initialization parameters may be used to calculate and qualify a physiological rate. The system may use signal conditioning to reduce noise in the physiological signal and to improve the determination of physiological information. The system may use qualification techniques to confirm determined physiological parameters. The system may also use autocorrelation techniques, cross-correlation techniques, fast start techniques, and/or reference waveforms when processing the physiological signal.