A 32-electrode data collection system for electrical impedance tomography.

A 32-electrode data collection system for Electrical Impedance Tomography (EIT) will be presented. In this system, the demodulator is a multiplexed sample and hold (S&H) circuit followed by a voltage difference stage. This configuration provides high CMRR due to the low (almost DC) operating frequency of the signals the difference stage is required to process.

A reconstruction algorithm of electrical impedance tomography with optimal configuration of the driven electrodes.

A reconstruction algorithm for electrical impedance tomography (EIT) is presented. The least-squares (LS) method is applied and a formulation similar to that of the perturbation method is found. The main difference from perturbation lies with the sensitivity matrix, which here is replaced by the Jacobian matrix, defined in terms of the partial derivatives of every sensing electrode pair voltage difference with respect to every element's conductivity. The mutual position between the active electrodes is chosen to give optimum sensitivity. The results shown that the algorithm presented here has a better convergence and needs fewer iterations than the perturbation method.

Differential synchronous demodulation for electrical impedance tomography.

A differential synchronous demodulator developed for electrical impedance tomography applications is presented. The demodulator proves to have high CMRR due to its architecture.

Performance of a differential synchronous demodulator for electrical impedance tomography.

The performance of a differential synchronous demodulator is presented. This demodulator is part of an electrical impedance tomography system developed by our group. In addition a technique for common-mode correction instead of common-mode feedback is proposed. A series of measurements as a function of the common-mode signal is given.

Reconstruction of impedance images using a modified perturbation method.

A modified perturbation method (MPM) arising from the replacement of the sensitivity matrix by the Jacobian matrix is presented. Our results have been made using an array processor board with four T-800 INMOS transputers. The numerical algorithm has been matched to the new system and the procedure reached a minimum 50 times faster than for a single PC/AT with mathematical co-processor. Several phantoms have been reconstructed. From the results one can see the applicability of the MPM algorithm to complicated models.