Non-invasive sensing and reliable estimation of physiological parameters are important features of hemodialysis machines, especially for therapy customization (biofeedback). In this work, we present a new method for joint estimation of two important hemodialysis-related physiological parameters: relative blood volume and plasma sodium concentration. Methods: Our method makes use of a non-invasive sensor setup and of a mathematical estimator. The estimator, based on the Kalman filter, allows to merge data from multiple sensors, newly-designed as well as on-board, with modeling knowledge about the hemodialysis process. The system was validated on in-vitro hemodialysis sessions using bovine blood. Results: The estimation error we obtained (0.97±0.73% on relative blood volume and 0.47±0.19 mM on plasmatic sodium) proved to be comparable with that of reference data for both parameters: the system is sufficiently accurate to be relevant in a clinical context. Conclusion: Our system has the potential to provide accurate and important information on the state of a patient undergoing hemodialysis, while only low-cost modifications to the existing on-board sensors are required. Significance: Through improved knowledge of blood parameters during hemodialysis, our method will allow better patient monitoring and therapy customization in hemodialysis.

A New Method for Continuous Relative Blood Volume and Plasma Sodium Concentration Estimation during Hemodialysis

Ravagli, Enrico;Severi, Stefano
2019

Abstract

Non-invasive sensing and reliable estimation of physiological parameters are important features of hemodialysis machines, especially for therapy customization (biofeedback). In this work, we present a new method for joint estimation of two important hemodialysis-related physiological parameters: relative blood volume and plasma sodium concentration. Methods: Our method makes use of a non-invasive sensor setup and of a mathematical estimator. The estimator, based on the Kalman filter, allows to merge data from multiple sensors, newly-designed as well as on-board, with modeling knowledge about the hemodialysis process. The system was validated on in-vitro hemodialysis sessions using bovine blood. Results: The estimation error we obtained (0.97±0.73% on relative blood volume and 0.47±0.19 mM on plasmatic sodium) proved to be comparable with that of reference data for both parameters: the system is sufficiently accurate to be relevant in a clinical context. Conclusion: Our system has the potential to provide accurate and important information on the state of a patient undergoing hemodialysis, while only low-cost modifications to the existing on-board sensors are required. Significance: Through improved knowledge of blood parameters during hemodialysis, our method will allow better patient monitoring and therapy customization in hemodialysis.
2019
Ravagli, Enrico; Holmer, Mattias; Sornmo, Leif; Severi, Stefano
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/689823
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