Adaptive Aortic Pressure Waveform Estimation via Diastolic Flow Minimization
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Solution Overview
Problem
Current methods for determining central aortic pressure waveforms from peripheral artery pressure waveforms are limited by wave reflections and inter-subject and temporal variability in the arterial tree, leading to inaccuracies in clinical measurements.
Innovation Solution
A method using a distributed model to derive a pressure-to-pressure and pressure-to-flow transfer function, with parameters estimated to minimize central arterial flow during diastole, allowing for adaptive transformation of peripheral artery pressure waveforms to aortic pressure waveforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a generalized transfer function is used to derive AP waveform from PAP waveform, then the method is simple to implement, but measurement precision deteriorates due to inter-subject and temporal variability in arterial tree properties
Solution Approach 1:
The patent applies dynamics by making the transfer function adaptive rather than static. The system continuously updates the transfer function parameters based on real-time analysis of the PAP waveform, allowing the model to adapt to temporal variations in arterial tree properties. This resolves the contradiction by maintaining ease of implementation through automated adaptation while significantly improving measurement precision through subject-specific parameter estimation.
Solution Approach 2:
The patent changes parameters by estimating subject-specific arterial tree properties (such as wave reflection coefficients and propagation velocities) from the PAP waveform, rather than using fixed generalized parameters. This allows the transfer function to be customized for each subject and updated over time, resolving the contradiction between simple implementation and accurate measurement by automating the parameter adaptation process.
2Device complexity
If arterial tree properties are assumed invariant over time and between individuals, then the transfer function method is computationally simple, but reliability deteriorates due to known physiological variability
Solution Approach 1:
The patent resolves this contradiction by implementing a dynamic adaptation mechanism that automatically updates transfer function parameters based on observed PAP waveform characteristics. This maintains computational simplicity through automated algorithms while improving reliability by accounting for physiological variability in arterial tree properties over time and between subjects.
Solution Approach 2:
The system applies self-service by using the PAP waveform itself to automatically estimate and update the transfer function parameters without requiring external input or manual calibration. This maintains low computational complexity while significantly improving reliability through subject-specific adaptation to actual physiological conditions.
Data Source
AI summary
A method is provided for determining a central aortic pressure (AP) wave-form for a subject. The method includes measuring a peripheral artery pressure (PAP) waveform from the subject, employing a distributed model to define a pressure-to-pressure transfer function relating PAP to AP and a pressure-to-flow transfer function relating PAP to a central arterial flow in terms of the same unknown parameters, estimating the unknown parameters by finding the pressure-to-flow transfer function, which when applied to the measured PAP waveform, minimizes the magnitude of the central arterial flow waveform during diastole, and applying the pressure-to-pressure transfer function with the estimated parameters to determine an AP waveform for the subject.