Classifying lung congestion in congestive heart failure using electrical impedance - A 3D model

Noam Omer*, Shimon Abboud, Marina Arad

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


In congestive heart failure (CHF) patients an increased interstitial fluid leads to collection of large amounts of fluids in the lungs which are major cause of mortality. Classifying and monitoring pulmonary congestions is a significant clinical challenge, due to lack of direct access to the pleural cavity. In this study, we investigate the feasibility of the Parametric Electrical Impedance Tomography (pEIT) technique in classifying and monitoring pleural effusion. The investigation is based on pEIT with a reduced number of electrodes applied in a computerized 3D model of the human thorax. The Forward Problem for Poisson's equation was implemented using Finite Volume Method (FVM) to estimate the potentials developed on the body surface. Significant linear regression (r-square>0.81) was found in 7 and 6 out of 8 independent projections for the right and the left lung, respectively, indicating an increase in surface potential while increasing lungs fluids. Moreover, the study results show that the projection's sensitivity is higher for cross sectional projections during pleural effusion. Hence, monitoring and classifying pleural effusion can be achieved with the pEIT technique making it feasible in monitoring lung fluid status in patients with pleural effusion.

Original languageEnglish
Title of host publicationComputing in Cardiology Conference 2015, CinC 2015
EditorsAlan Murray
PublisherIEEE Computer Society
Number of pages4
ISBN (Electronic)9781509006854
StatePublished - 16 Feb 2015
Event42nd Computing in Cardiology Conference, CinC 2015 - Nice, France
Duration: 6 Sep 20159 Sep 2015

Publication series

NameComputing in Cardiology
ISSN (Print)2325-8861
ISSN (Electronic)2325-887X


Conference42nd Computing in Cardiology Conference, CinC 2015


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