Medical Sensor Signal Normalization for FFR Measurement Quality
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Solution Overview
Problem
Current methods for measuring fractional flow reserve (FFR) and instantaneous wave-free ratio (iFR) in blood vessels face challenges in ensuring the quality and trustworthiness of pressure measurements due to inter-sensor variability and anomalies, which can lead to incorrect assessments of stenosis severity.
Innovation Solution
An apparatus and method that normalize temporal measurement signals from multiple sensors within a blood vessel, calculate a figure of merit based on shape deviations, and provide feedback to users on measurement quality, allowing for corrective actions to improve reliability and trustworthiness of FFR or iFR assessments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pressure measurements are taken using multiple sensors in blood vessels, then FFR or iFR values can be calculated to assess stenosis severity, but inter-sensor variability and measurement anomalies reduce the reliability and trustworthiness of the measurements
Solution Approach 1:
The system calculates a figure of merit based on shape deviation between normalized temporal measurement signals and provides feedback to users about measurement quality. This feedback mechanism allows operators to assess whether measurements are trustworthy and take corrective actions if quality is insufficient, directly addressing the reliability issue while maintaining measurement precision capabilities
Solution Approach 2:
The system normalizes temporal measurement signals by adjusting parameters such as amplitude and time alignment to account for inter-sensor variability. By changing these signal parameters through normalization, the system compensates for sensor differences and improves both measurement precision and reliability simultaneously
2Measurement precision
If normalization of temporal measurement signals is performed to account for inter-sensor variability, then measurement quality improves, but additional processing steps and computational complexity are introduced
Solution Approach 1:
The normalization process is performed automatically by the system itself without requiring external intervention or complex manual calibration. The system self-adjusts signal parameters and automatically calculates the figure of merit, reducing operational complexity while maintaining improved measurement precision
Solution Approach 2:
The system replaces complex manual calibration procedures with automated digital signal processing algorithms. By substituting mechanical/manual normalization steps with computational methods, the system improves measurement precision while actually reducing overall system complexity
3Reliability
If a figure of merit is calculated based on shape deviation to assess measurement quality, then users can make informed decisions about measurement trustworthiness, but additional computational steps are required
Solution Approach 1:
The figure of merit calculation is performed automatically as part of the measurement process before final assessment decisions are made. By conducting this quality assessment preliminarily and automatically, the system enables informed decision-making without requiring additional manual computational steps, thus maintaining workflow efficiency while improving assessment accuracy
Data Source
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AI summary
An apparatus (6) connectable to a medical instrument (5) is configured to ascertain a figure of merit (22) based on a shape deviation between the temporal measurement signals (11,13) after normalization, wherein the temporal measurement signals (11,12) are received form sensors (56,57) integrated into the medical instrument (5). A system comprising the apparatus and a method of ascertaining the figure of merit are further presented.