Physiological Sensor Multiple Measurement Mode for Accuracy
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Solution Overview
Problem
Pulse oximetry measurements are prone to errors due to sensor misplacement and environmental factors, which can lead to inaccurate predictions of blood oxygen saturation and pulse rate, especially in scenarios with motion-induced noise.
Innovation Solution
A physiological sensor system that takes multiple measurements at various wavelengths, allowing for recalibration between measurements to improve accuracy, discards potentially erroneous data points, and uses statistical methods to calculate a final predicted parameter value, such as the median or mean, to reduce the impact of sensor misplacement and environmental factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple measurements are taken to improve accuracy, then measurement precision is improved, but loss of time increases due to repeated measurements and sensor reapplication
Solution Approach 1:
The system performs preliminary validation checks on measurement data to identify potentially erroneous readings before they are used in final calculations. This allows for early detection of problematic measurements and enables targeted reapplication of the sensor only when necessary, rather than requiring multiple full measurement cycles.
Solution Approach 2:
The system discards potentially erroneous measurement results based on validation criteria (such as physiological plausibility checks or signal quality assessment) and recovers by taking additional measurements only when needed. This selective approach maintains accuracy while minimizing unnecessary time loss from redundant measurements.
2Reliability
If sensor reapplication is performed between measurements to decrease erroneous predictions, then reliability is improved, but device complexity increases due to additional operational steps
Solution Approach 1:
The system implements feedback mechanisms that monitor measurement quality and provide information about sensor placement adequacy. This feedback loop allows the system to automatically determine when sensor reapplication is necessary, reducing the need for complex manual protocols and enabling intelligent, condition-based decision making about when to repeat measurements.
Solution Approach 2:
The measurement system performs self-validation through automated checks of measurement quality and physiological plausibility. This self-service capability allows the system to identify and flag potentially erroneous measurements without requiring complex external validation procedures, thereby improving reliability while maintaining operational simplicity.
3Measurement precision
If statistical methods are used to calculate final predicted parameter value, then measurement precision is improved, but loss of time increases due to data processing
Solution Approach 1:
The system applies statistical processing selectively rather than to all measurements uniformly. By using validation criteria to identify and exclude potentially erroneous measurements before statistical calculation, the system achieves improved precision through targeted processing of only the necessary data subset, thereby reducing overall processing time while maintaining accuracy.
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 enhances the accuracy and reliability of blood oxygen saturation and pulse rate measurements by minimizing the effect of sensor placement errors and environmental factors, providing a more confident and precise estimation of physiological parameters.
Implementation Method 1
Spectroscopy is a common technique for measuring the concentration of organic and some inorganic constituents of a solution. The theoretical basis of this technique is the Beer-Lambert law, which states that the concentration ci of an absorbent in solution can be determined by the intensity of light transmitted through the solution
Implementation Method 2
The theoretical basis of this technique is the Beer-Lambert law, which states that the concentration ci of an absorbent in solution can be determined by the intensity of light transmitted through the solution, knowing the pathlength dλ, the intensity of the incident light I0,λ, and the extinction coefficient εi,λ at a particular wavelength λ
Data Source
AI summary
In a physiological sensor that estimates a true parameter value by providing a predicted parameter value, multiple measurements are taken to increase the accuracy of the predicted parameter value. The sensor can be reapplied between measurements to decrease the probability of an erroneous prediction caused by sensor misplacement. Some measurements can be discarded before calculating a predicted parameter value. The physiological sensor can have a plurality of modes, with one of the modes corresponding to multiple measurement process.