Sensitivity analysis study on the effect of the fluid mechanics assumptions for the computation of electrical conductivity of flowing human blood

Gian Marco Melito*, Thomas Stephan Müller, Vahid Badeli, Katrin Ellermann, Günter Brenn, Alice Reinbacher-Köstinger

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Impedance cardiography is a non-invasive methodology for measuring cardiodynamic parameters, such as stroke volume and heart rate, as well as cardiac output. For the measurement, the electric conductivity of blood is important. The conductivity of blood depends on various parameters, such as the haematocrit value as well as the red blood cells’ (RBC) shape and orientation. In models, the response is usually affected by uncertainty, which may lead to inaccurate medical diagnosis. Therefore, a ranking of the influence of the model’s input factors may be necessary. Also, physically and physiologically correct assumptions are fundamental for the accuracy of the model. The basis for predicting the conductivity of blood in this study is the Maxwell–Fricke theory, which allows computing the electrical bulk conductivity of quiescent blood. For flowing blood, fluid mechanics has to be coupled in the modelling phase.
Nevertheless, some assumptions may lead to invalid or inaccurate results. Based on a global sensitivity analysis, this work shows which fluid mechanical assumptions are incorrect and should be avoided. Moreover, positive effects based on accurate rheological modelling of the fluid properties are shown, and the factors with a decisive influence on the computed conductivity change of flowing blood are illustrated.
Original languageEnglish
Article number107663
Number of pages12
JournalReliability Engineering & System Safety
Early online date27 Mar 2021
Publication statusPublished - Sept 2021


  • Sensitivity analysis
  • Blood conductivity
  • fluid mechanics
  • Polynomial chaos expansion
  • Fluid mechanics

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering

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