Physiological Signal Qualification via Statistical Metric Analysis
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Solution Overview
Problem
Physiological monitors face challenges in accurately determining pulse rates from photoplethysmographic signals due to noise components, subject movement, and varying pulse shapes, especially in subjects with low perfusion or dicrotic notches, which can lead to incorrect rate determination.
Innovation Solution
The implementation of a physiological monitor with a processing module that employs multiple operating modes, band-pass filtering, and qualification techniques to filter out noise, adjust algorithm settings based on signal analysis, and manage status flags to ensure accurate pulse rate determination, even in noisy conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If band-pass filtering is applied to reject noise, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent implements dynamic adjustment of band-pass filter parameters based on the detected pulse rate. The filter's center frequency and bandwidth are continuously adapted to track the physiological signal characteristics, allowing the system to maintain high measurement precision while avoiding the complexity of fixed multi-filter configurations. This dynamic adaptation enables a single filter to perform the work of multiple static filters.
Solution Approach 2:
The system changes the parameters of the band-pass filter (center frequency, bandwidth) based on the analyzed pulse rate and signal characteristics. By dynamically modifying these parameters, the filter optimally rejects noise at different frequencies while passing the physiological signal, resolving the contradiction between precision and complexity.
2Reliability
If multiple operating modes with strict criteria are used to ensure accurate parameter determination, then reliability is improved, but productivity decreases
Solution Approach 1:
The patent implements a hierarchical qualification process where initial gross error checks are performed first, followed by progressively stricter validation criteria only when needed. This preliminary filtering of obvious errors allows the system to quickly reject clearly invalid measurements while applying more time-consuming strict criteria only to borderline cases, thereby maintaining high reliability without completely sacrificing productivity.
Solution Approach 2:
The system applies different levels of qualification strictness based on the confidence level of the measurement. For high-confidence measurements, minimal qualification is applied, while for uncertain measurements, full strict criteria are enforced. This partial application of excessive action ensures reliability is maintained only where necessary, improving overall productivity.
3Adaptability or versatility
If algorithm settings are adjusted based on signal analysis to handle varying pulse shapes, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent implements self-adjusting algorithm parameters that automatically adapt to different pulse shapes and signal conditions. The system analyzes the incoming signal characteristics (amplitude, frequency, morphology) and autonomously configures the processing parameters without requiring external intervention or complex pre-programming for each scenario. This self-service approach improves adaptability while limiting complexity growth.
Solution Approach 2:
The system continuously monitors the quality of parameter determination and uses this feedback to dynamically adjust algorithm settings. When measurement quality degrades, the system automatically modifies processing parameters to restore accuracy, creating a closed-loop adaptive system that handles varying pulse shapes without manual reconfiguration.
4Measurement precision
If qualification techniques are applied to prevent band-pass filter tuning to noise, then measurement precision is improved, but loss of time occurs
Solution Approach 1:
The patent performs preliminary qualification checks on the detected pulse rate before finalizing the measurement. These preliminary checks include verifying the rate falls within physiological ranges and assessing signal quality metrics. By performing these checks early in the processing pipeline, the system prevents wasted time on clearly invalid measurements and only applies more time-consuming verification to potentially valid results.
Solution Approach 2:
The system implements a fast-path qualification process that quickly validates obvious cases and only applies full verification to borderline cases. When the initial assessment strongly indicates a valid measurement, the system skips detailed verification steps, rushing through to the result. This selective approach maintains precision while minimizing time loss on clear cases.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables reliable determination of pulse rates by effectively filtering noise and adjusting to changing physiological conditions, ensuring accurate and stable output even in challenging scenarios.
Implementation Method 1
A sensor, having a detector, which generates an intensity signal (e.g., a PPG signal) based on light attenuated by the subject
Data Source
AI summary
A physiological monitoring system may determine physiological information, such as physiological rate information, from a physiological signal. The system may receive a calculated value indicative of a physiological rate. The system may generate value pairs from a first collection of values of the physiological signal and another collection of corresponding value of the physiological signal spaced from the first collection based on the calculated value. The system may determine a best fit linear relationship based on the value pairs and determine at least one statistical metric based on the linear relationship and the value pairs. The system may qualify or disqualify the calculated value based on the at least one statistical metric.