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Updated: Jan 20, 2026
Thermal Measurement Techniques in Analytical Microfluidic Devices
Published on: June 3, 2015
Microfluidics-based device for the measurement of blood viscosity and its modeling based on shear rate, temperature,
Ruba Khnouf1, Dina Karasneh2,3, Enas Abdulhay2
1Department of Biomedical Engineering, Faculty of Engineering, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan. rekhnouf@just.edu.jo.
Blood viscosity measurements are crucial for the diagnosis and understanding of a range of hematological and cardiovascular diseases. Such measurements are heavily used in monitoring patients during and after surgeries, which necessitates the development of a highly accurate viscometer that uses a minimal amount of blood. In this work, we have designed and implemented a microfluidic device that was used to measure fluid viscosity with a high accuracy using less than 10 μl of blood. The device was further used to construct a blood viscosity model based on temperature, shear rate, and anti-coagulant concentration. The model has an R-squared value of 0.950. Finally, blood protein content was changed to simulate diseased conditions and blood viscosity was measured using the device and estimated using the model constructed in this work. Simulated diseased conditions were clearly detected when comparing estimated viscosity values using the model and the measured values using the device, proving the applicability of the setup in the detection of rheological anomalies and in disease diagnosis.
Blood viscosity measurements are crucial for the diagnosis and understanding of a range of hematological and cardiovascular diseases. Such measurements are heavily used in monitoring patients during and after surgeries, which necessitates the development of a highly accurate viscometer that uses a minimal amount of blood. In this work, we have designed and implemented a microfluidic device that was used to measure fluid viscosity with a high accuracy using less than 10 μl of blood. The device was further used to construct a blood viscosity model based on temperature, shear rate, and anti-coagulant concentration. The model has an R-squared value of 0.950. Finally, blood protein content was changed to simulate diseased conditions and blood viscosity was measured using the device and estimated using the model constructed in this work. Simulated diseased conditions were clearly detected when comparing estimated viscosity values using the model and the measured values using the device, proving the applicability of the setup in the detection of rheological anomalies and in disease diagnosis.
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