Extracorporeal Blood Temperature Sensing with Flow-Rate Compensation
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Solution Overview
Problem
Existing extracorporeal blood treatment systems face challenges in accurately measuring and controlling patient core temperature due to heat transfer variations in the blood circuit, especially when temperature sensors are located remotely from the patient, leading to inaccuracies in temperature readings.
Innovation Solution
A method that involves measuring blood temperature at different flow rates and using thermal models to calculate the core temperature, incorporating heat transfer coefficients and ambient temperature estimation to correct for heat loss or gain, allowing for precise core temperature estimation and feedback-controlled temperature regulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If temperature sensors are located remotely from the patient in the blood circuit, then the system can operate with simplified temperature measurement setup, but the temperature readings become inaccurate due to heat transfer variations in the blood circuit
Solution Approach 1:
The system measures temperature at multiple different blood flow rates (changing the flow parameter) to obtain multiple temperature readings. By varying the flow rate parameter, the system can calculate heat transfer coefficients and compensate for heat loss, thereby improving measurement accuracy while maintaining remote sensor placement
Solution Approach 2:
The system uses the temperature readings obtained at different flow rates to calculate heat transfer coefficients and ambient temperature. This calculated information is then fed back to correct the temperature measurement, compensating for heat transfer effects in the blood circuit and improving the accuracy of the patient's core temperature determination
2Measurement precision
If thermal models with heat transfer coefficients and ambient temperature estimation are used to calculate core temperature, then accurate core temperature estimation is achieved, but the system complexity increases
Solution Approach 1:
The system determines its own operating parameters (heat transfer coefficient and ambient temperature) by performing measurements at different flow rates during normal operation. This self-determination eliminates the need for external calibration equipment or complex manual setup, reducing system complexity while maintaining high measurement accuracy
3Measurement precision
If multiple temperature measurements at different flow rates are taken to calculate heat transfer rate, then accurate inlet temperature is determined, but the measurement time increases
Solution Approach 1:
The system performs temperature measurements at different flow rates in a periodic sequence during normal blood treatment operation. The measurements are integrated into the routine operation cycles, allowing accurate temperature determination without adding significant time loss to the overall treatment process
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables accurate estimation and regulation of patient core temperature, even with remote temperature sensing, reducing errors and ensuring effective temperature management during extracorporeal blood treatments.
Implementation Method 1
a temperature sensor (116) positioned remote from a patient's core and configured to indicate a temperature of blood flowing through a blood circuit
Implementation Method 2
heat transfer between the blood and the external environment of the blood circuit
Implementation Method 3
temperature change of the blood in the blood circuit due to heat gain or loss caused by heat transfer between the blood and the external environment
Data Source
AI summary
A core temperature measurement may be made by varying the heat transfer dynamics of a blood circuit and fitting parameters of a blood circuit heat transfer configuration to measurements under the varied conditions. Then the input temperature of the patient core can be extracted from the model and a current temperature measurement remote from the patient core and optionally other measurements such as blood flow rate.