Blood Pump Parameter Estimation for Dynamic Flow and Pressure Sensing
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Solution Overview
Problem
Existing blood pump technologies face challenges in accurately determining blood flow, pressure difference, and viscosity, especially during dynamic or changing states, as most methods rely on static models and separate sensors, which are costly and ineffective in dynamic conditions.
Innovation Solution
A method using dynamic models with interlinked differential equations to estimate operational parameters like rotational speed, axial deflection, and drive power, incorporating a Kalman filter for continuous measurement and estimation, allowing for the determination of blood flow, pressure difference, and viscosity even in changing conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate sensors are used to measure blood flow, pressure difference, and viscosity, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The blood pump system uses its own operational parameters (rotational speed, drive power, axial deflection) to determine blood flow, pressure difference, and viscosity, rather than requiring separate measurement sensors. The system serves its own measurement needs through the estimation unit that processes operational data to derive physiological parameters.
Solution Approach 2:
The operational parameters measurement unit serves multiple functions: it measures rotational speed, drive power, and axial deflection for both pump control purposes and physiological parameter determination. This multi-functional approach eliminates the need for dedicated separate sensors for each physiological parameter.
2Device complexity
If static models are used to determine operational parameters, then device complexity is reduced, but measurement precision deteriorates during dynamic states
Solution Approach 1:
The system transitions from static characteristic curve models to dynamic estimation using interlinked differential equations. The estimation unit continuously updates physiological parameters based on real-time operational parameter changes, enabling accurate determination during dynamic states while the pump transitions between operating conditions.
Solution Approach 2:
The system uses feedback from operational parameters (rotational speed, drive power, axial deflection) to continuously estimate and update physiological parameters. The estimation unit processes current operational data to determine current physiological states, enabling adaptive response to changing conditions.
3Measurement precision
If dynamic models with differential equations are used, then measurement precision during dynamic states is improved, but device complexity and computational requirements increase
Solution Approach 1:
The system combines the operational parameters measurement unit with the estimation unit into an integrated determination system. The measurement and estimation functions are merged, allowing the system to process operational data and derive physiological parameters within a unified computational framework that manages complexity.
Solution Approach 2:
The estimation unit acts as an intermediary that translates operational parameters into physiological parameters using differential equations. This intermediary layer processes the complex mathematical relationships between measurable operational quantities and desired physiological parameters, shielding the overall system from the full complexity of the dynamic models.
4Measurement precision
If operational parameters are monitored continuously, then measurement precision during changing states is improved, but loss of time for data processing increases
Solution Approach 1:
The system maintains continuous monitoring and estimation of operational parameters without interruption during pump operation. The estimation unit continuously processes operational data to determine physiological parameters, ensuring uninterrupted measurement precision even during dynamic transitions and pump startup/shutdown phases.
Data Source
AI summary
Methods and apparatuses for determining operational parameters of a blood pump comprising a rotor which transports the blood are provided. The change in the behaviour of at least one first and one second operational parameter, independently from each other, of the pump, is determined. A determination of the flow through the pump and/or the difference in pressure across the pump and/or the viscosity of the blood takes into account the determined change in behaviour of the at least two operational parameters. A modelling for a dynamic model of the known quantities may be carried out and an estimation method using a Kalman filter may be used.