Next Article in Journal
Expanding Bias-instability of MEMS Silicon Oscillating Accelerometer Utilizing AC Polarization and Self-Compensation
Next Article in Special Issue
Combination of Sensor Data and Health Monitoring for Early Detection of Subclinical Ketosis in Dairy Cows
Previous Article in Journal
Human Vital Signs Detection Methods and Potential Using Radars: A Review
Previous Article in Special Issue
Design and Calibration of an Instrumented Seat Post to Measure Sitting Loads While Cycling
Article

Estimation Methods for Viscosity, Flow Rate and Pressure from Pump-Motor Assembly Parameters

1
Institute of Engineering Design and Product Development, TU Wien, 1060 Vienna, Austria
2
Institute of Chemical, Environmental and Bioscience Engineering, TU Wien, 1060 Vienna, Austria
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(5), 1451; https://doi.org/10.3390/s20051451
Received: 31 January 2020 / Revised: 24 February 2020 / Accepted: 28 February 2020 / Published: 6 March 2020
(This article belongs to the Special Issue Sensors for Biomechanics Application)
Blood pumps have found applications in heart support devices, oxygenators, and dialysis systems, among others. Often, there is no room for sensors, or the sensors are simply unreliable when long-term operation is required. However, control systems rely on those hard-to-measure parameters, such as blood flow rate and pressure difference, thus their estimation takes a central role in the development process of such medical devices. The viscosity of the blood not only influences the estimation of those parameters but is often a parameter that is of great interest to both doctors and engineers. In this work, estimation methods for blood flow rate, pressure difference, and viscosity are presented using Gaussian process regression models. Different water–glycerol mixtures were used to model blood. Data was collected from a custom-built blood pump, designed for intracorporeal oxygenators in an in vitro test circuit. The estimation was performed from motor current and motor speed measurements and its accuracy was measured for: blood flow rate r2 = 0.98, root mean squared error (RMSE) = 46 mL.min−1; pressure difference r2 = 0.98, RMSE = 8.7 mmHg; and viscosity r2 = 0.98, RMSE = 0.049 mPa.s. The results suggest that the presented methods can be used to accurately predict blood flow rate, pressure, and viscosity online. View Full-Text
Keywords: blood pumps; flow rate; pressure difference; viscosity; estimation; Gaussian process regression blood pumps; flow rate; pressure difference; viscosity; estimation; Gaussian process regression
Show Figures

Figure 1

MDPI and ACS Style

Elenkov, M.; Ecker, P.; Lukitsch, B.; Janeczek, C.; Harasek, M.; Gföhler, M. Estimation Methods for Viscosity, Flow Rate and Pressure from Pump-Motor Assembly Parameters. Sensors 2020, 20, 1451. https://doi.org/10.3390/s20051451

AMA Style

Elenkov M, Ecker P, Lukitsch B, Janeczek C, Harasek M, Gföhler M. Estimation Methods for Viscosity, Flow Rate and Pressure from Pump-Motor Assembly Parameters. Sensors. 2020; 20(5):1451. https://doi.org/10.3390/s20051451

Chicago/Turabian Style

Elenkov, Martin, Paul Ecker, Benjamin Lukitsch, Christoph Janeczek, Michael Harasek, and Margit Gföhler. 2020. "Estimation Methods for Viscosity, Flow Rate and Pressure from Pump-Motor Assembly Parameters" Sensors 20, no. 5: 1451. https://doi.org/10.3390/s20051451

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop