A realistic three dimensional FEM of the human head.

A realistic three-dimensional finite element model (FEM) of the human head has been developed. Separate layers for the scalp, skull, cerebrospinal fluid (CSF) and brain were modelled. Hexahedral elements, a special master matrix assembly technique and an iterative successive over-relaxation (SOR) solution scheme were employed. This approach enabled rapid modelling with minimal memory requirements, which makes this method practical if used for electrical impedance tomography (EIT) or source localization inverse problems. Compared to scalp electrodes, subdural voltage sensing electrodes were three to four times more sensitive close to an oedema or source region, if it was peripheral, but this decreased to 30%-40% for central oedema or source regions. Scalp current injecting electrodes are preferable, since the maximum allowable current is 10 times larger than that of the subdural ones. The distance of voltage sensing electrodes from a region to be imaged highly affects sensitivity, so depth electrodes will be more sensitive, provided that they are close to the region of interest. Finally, the electrode size has significant effects on the input or transfer impedance.

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.

An efficient finite-element algorithm for 3D layered complex structure modelling.

In this paper an efficient finite-element method (FEM) algorithm for complicated three-dimensional (3D) layered type models has been developed. Its unique feature is that it can handle, with memory requirements within the abilities of a simple PC, arbitrarily shaped 3D elements. This task is achieved by storing only the non-zero coefficients of the sparse FEM system of equations. The algorithm is applied to the solution of the Laplace equation in models with up to 79 layers of trilinear general hexahedron elements. The system of equations is solved with the Gauss-Seidel iterative technique.

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.

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.