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We propose a measurement method using Walsh functions in 32-electrode electrical impedance tomography. By injecting currents in spatial Walsh function patterns, we use the simplicity of pulse type injection and yield the optimal SNR or distinguishability of sinusoidal injection. Once we measure boundary voltage data for the injection of all 31 patterns of Walsh functions, we can compute all 31 optimal current pattems. We can also synthesize the voltage data due to the injection of the optimal current patterns without actually injecting the optimal current patterns.

The use of compound electrodes to improve the conditioning and sensitivity of an electrical impedance tomography imaging system is described. Effects of electrode-skin contact impedance are discussed and a model is proposed. Reconstructed static images from phantoms are shown. >

An electrical impedance tomography (EIT) method is considered in which 32 electrodes are placed around the thorax, currents are injected, and voltages are measured to reconstruct a cross-sectional image of resistivity. The authors solve the forward problem using the finite-element method (FEM). The number of elements determines the spatial resolution of the resistivity image. An adaptive current-injection method to provide an optimal current distribution is used. The modified Newton-Raphson method is used as the reconstruction algorithm. The authors use sparse matrix techniques with node renumbering methods to minimize the computation time. >