Physiological Sensor Validation Using Stored Feature Parameters
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Solution Overview
Problem
Current solutions for validating physiological sensors in patient monitors struggle to balance patient safety with manufacturing yield, as tight acceptance criteria are necessary to prevent the use of aged or unauthorized sensors but result in increased costs and reduced yield.
Innovation Solution
A method involving the determination and storage of sensor feature parameters, such as the ratio of current transfer ratios, prior to use, and subsequent comparison with values measured during connection to a patient monitor, allowing for real-time validation and decision-making on sensor acceptance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If tight acceptance criteria are applied to sensor parameters to ensure patient safety, then sensor quality and reliability are improved, but manufacturing yield decreases and product costs increase
Solution Approach 1:
The patent applies preliminary action by measuring and storing sensor feature parameters during the manufacturing process before the sensor is deployed. This allows the sensor's actual performance characteristics to be captured and stored in its memory, enabling later validation without requiring tight acceptance criteria that would reject sensors with normal manufacturing variations. The sensor is prepared in advance with its own reference values for future comparison.
Solution Approach 2:
The patent implements parameter changes by shifting from fixed acceptance criteria to dynamic, sensor-specific validation. Instead of using predetermined threshold values for sensor parameters, the system measures actual sensor feature parameters (such as optical properties, electrical characteristics, or performance metrics) during manufacturing, stores these values in the sensor's memory, and uses them as the basis for validation during use. This allows each sensor to be validated against its own characteristics rather than generic thresholds.
2Productivity
If wide acceptance criteria are used to improve manufacturing yield, then productivity increases, but patient safety may be compromised due to inclusion of low-quality sensors
Solution Approach 1:
The patent implements feedback by creating a closed-loop validation system. Sensor feature parameters are measured during manufacturing and stored in the sensor's memory. During subsequent use, the patient monitor retrieves these stored values and compares current sensor performance against the stored reference values. This feedback mechanism ensures that only sensors maintaining their original performance characteristics are accepted, while sensors that have degraded or been tampered with are rejected, thereby ensuring patient safety without requiring overly restrictive initial acceptance criteria.
3Reliability
If sensor validation mechanisms are implemented to prevent use of unauthorized or aged sensors, then patient safety is improved, but device complexity and manufacturing costs increase
Solution Approach 1:
The patent applies self-service by enabling the sensor to validate itself without requiring complex external validation infrastructure. The sensor contains its own stored feature parameters in its memory and performs self-validation when connected to the patient monitor. The monitor simply retrieves the stored values and compares them with current measurements, allowing the sensor to essentially validate its own integrity. This eliminates the need for complex centralized validation systems or additional hardware components.
Solution Approach 2:
The patent uses preliminary action by pre-storing validation data in the sensor's memory during manufacturing. This includes sensor identification information, feature parameters, and reference values that enable future validation. By preparing this validation data in advance, the system avoids the need for complex real-time validation mechanisms or external databases, simplifying the overall system architecture while maintaining robust safety validation.
Data Source
AI summary
In order to increase sensor manufacturing yield without compromising patient safety, at least one first value is determined respectively for at least one sensor feature parameter indicative of characteristics of a physiological sensor and the determined value(s) is/are stored in a predefined memory location prior to use of a physiological sensor. In response to the physiological sensor being connected to a patient monitor, at least one second value is defined respectively for the at least one sensor feature parameter and the at least one first value of each of the at least one sensor feature parameter is retrieved from the predefined memory location. Each of the at least one second value is compared with respective at least one first value and a decision is made, based on the comparison, on the acceptance of the physiological sensor.