Monitoring lungs with electrical impedance tomography

Abstract

To monitor lungs, a real-time device based on applied potential must be able to detect conductivity variations in any area (cm2) inside the thorax at each 40 ms. An image, that represents the conductivity distribution of a transversal slice of the thorax, is reconstructed based on applied current and voltage measurements on the boundary. The quality of the image is strongly related with the total number of electrodes and regularization techniques. In this work, the total number of independent measurements is improved by an interpolation scheme applied to the measured voltages, to simulate extra electrodes and preserve the dipole model for electrical potential. Comparison parameters are the object position and maximum conductivity of the reconstructed image. The technique is applied to experimental and simulated data using backprojection algorithm, demonstrating a significant improvement of the images. Only a neighborhood filter is applied to all images to enhance the backprojection reconstruction.