Physiological Signal Qualification via Cross-Correlation Search
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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, especially in subjects with low perfusion or neonates, which can lead to incorrect rate calculations.
Innovation Solution
The system employs a dual-mode processing approach using a search mode to determine initialization parameters and a locked mode to refine the pulse rate calculation, incorporating techniques such as autocorrelation, band-pass filtering, and cross-correlation analysis to isolate and qualify the physiological signal, thereby reducing noise interference and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If a relatively narrow band-pass filter is used to determine pulse rate, then noise rejection is improved, but the filter may be initially tuned to noise or deviate from the correct physiological rate
Solution Approach 1:
The system performs a search mode before locked mode to preliminarily identify the correct pulse rate range. This preliminary action ensures that when the narrow band-pass filter is subsequently tuned in locked mode, it starts from an accurate initialization parameter rather than potentially tuning to noise, thus resolving the contradiction between noise rejection and tuning accuracy
Solution Approach 2:
The system continuously monitors qualification metrics and provides feedback to adjust filter tuning. When the filter deviates from the correct physiological rate, the feedback mechanism detects this through qualification failure and triggers a return to search mode or parameter adjustment, maintaining reliable filter tuning while preserving noise rejection capabilities
2Measurement precision
If signal processing techniques are applied to qualify physiological parameters, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The signal processing is divided into distinct segments: search mode for initialization parameter determination and locked mode for refined pulse rate calculation with qualification. This segmentation allows complex processing to be organized in manageable stages, improving measurement precision through systematic qualification while making the device complexity more controllable and understandable
Solution Approach 2:
The system applies qualification techniques selectively - full qualification processing is applied only when needed to confirm pulse rate accuracy, rather than continuously. This partial action approach maintains measurement precision when required while reducing unnecessary processing complexity during stable operation
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.