Adaptive Pressure Transfer Function for Aortic Blood Pressure Reconstruction
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Solution Overview
Problem
Existing methods for reconstructing aortic blood pressure waveforms from peripheral measurements during exercise are inaccurate due to changes in the aortic-to-peripheral pressure transfer function, which are not adequately accounted for by generic transfer functions, leading to overestimation and unpredictability in systolic pressure measurements.
Innovation Solution
A method that determines individualized pressure transfer functions using pre-selected parameters from peripheral blood pressure waveforms, specifically adjusting the resonance peak frequency based on cardiac output and other hemodynamic parameters to accurately model the blood pressure transfer function in the frequency domain, thereby improving the accuracy of aortic blood pressure waveform reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed pressure transfer function is used for reconstructing aortic blood pressure during exercise, then the method is simple to implement, but the measurement precision deteriorates due to changes in the transfer function characteristics
Solution Approach 1:
The patent applies the dynamics principle by transitioning from a fixed pressure transfer function to an adaptive transfer function that dynamically adjusts its characteristics based on real-time peripheral blood pressure waveform parameters. The transfer function's resonance peak frequency is continuously adapted to match changing vascular conditions during exercise, ensuring accurate aortic pressure reconstruction across varying physiological states.
Solution Approach 2:
The patent implements parameter changes by modifying the pressure transfer function's characteristics (specifically the resonance peak frequency) based on detected changes in peripheral blood pressure waveform parameters. This allows the transfer function to adapt to exercise-induced vascular changes, maintaining measurement accuracy while keeping the implementation relatively straightforward.
2Device complexity
If a generic pressure transfer function is applied to all subjects, then the device complexity is reduced, but the measurement precision worsens due to individual variations in vascular properties
Solution Approach 1:
The patent applies local quality by customizing the pressure transfer function characteristics to match each subject's specific vascular properties. Instead of using a one-size-fits-all approach, the transfer function's resonance peak frequency is individually adapted based on each subject's peripheral blood pressure waveform parameters, accounting for inter-individual variations in arterial compliance and geometry.
Solution Approach 2:
The system implements self-service by automatically determining individualized transfer function parameters from the subject's own peripheral blood pressure waveform without requiring external calibration or complex subject-specific measurements. The adaptive algorithm extracts relevant parameters directly from the measured waveform and uses these to configure the transfer function appropriately for that subject.
3Measurement precision
If the resonance peak frequency of the pressure transfer function is adjusted during exercise, then the measurement precision improves, but the device complexity increases due to real-time parameter adaptation
Solution Approach 1:
The patent implements parameter changes by dynamically adjusting the pressure transfer function's resonance peak frequency based on real-time detection of peripheral blood pressure waveform parameter changes. This adaptation compensates for exercise-induced vascular modifications, maintaining accurate aortic pressure reconstruction while using a relatively simple algorithmic approach.
Solution Approach 2:
The system applies feedback by continuously monitoring peripheral blood pressure waveform parameters and using this information to adjust the pressure transfer function characteristics. The detected waveform parameters serve as feedback signals that drive the adaptation of the transfer function's resonance peak frequency, creating a closed-loop system that maintains accuracy during exercise.
Data Source
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AI summary
The invention relates to method for reconstructing an aortic blood pressure waveform of a person from a peripheral blood pressure waveform of the person comprising the steps of determining at least one pre-selected parameter of the peripheral blood pressure waveform, reconstructing the aortic blood pressure waveform from the peripheral blood pressure waveform using a pressure transfer function having at least one adjustable characteristics, wherein said adjustable characteristics is determined using the at least one pre-selected parameter of the peripheral blood pressure waveform. The invention further relates to a device for reconstructing an aortic blood pressure waveform from a peripheral blood pressure waveform and a computer program product.