Monitoring of lung edema using focused impedance spectroscopy: a feasibility study

Michael Mayer, Patricia Brunner, Robert Merwa, Hermann Scharfetter

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)


Currently only ionizing or invasive methods are used in clinical applications for the monitoring of extracellular lung water. Alternatively a method called focused conductivity spectroscopy (FCS) is suggested, which aims at reconstructing a pulmonary edema index (PEIX) by measuring the electrical conductivity of the region of interest (ROI) at several frequencies. In contrast to electrical impedance tomography (EIT) a minimum number of strategically placed electrodes is used. The goals of this study were the analysis of the sensitivity for the PEIX, an estimate of the optimal electrode configuration and the determination of the required frequencies. In order to calculate the solution of the FCS forward problem a realistic 3D model of a human torso was developed containing both lungs, the heart, the liver and the thorax musculature. The bioelectrical properties for each compartment were described with appropriate tissue models which relate the conductivity spectra to physiological parameters. The PEIX was defined as the interstitial volume fraction of the alveolar septa. Furthermore the model includes 48 electrodes subdivided into three layers. The optimal electrode configuration was selected by minimizing the number of electrodes, among certain subsets of these electrodes. The analysis shows that eight to ten electrodes and six frequencies are theoretically sufficient to obtain a coefficient of variation.

Original languageEnglish
Pages (from-to)185-192
Number of pages8
JournalPhysiological Measurement
Issue number3
Publication statusPublished - Jun 2005


  • EIT
  • Electrode optimization
  • Impedance
  • Lung edema
  • Spectroscopy


Dive into the research topics of 'Monitoring of lung edema using focused impedance spectroscopy: a feasibility study'. Together they form a unique fingerprint.

Cite this