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We propose the use of electrical impedance tomography (EIT) imaging techniques in the measurement of lung resistivity for detection and monitoring of apnea and edema. In EIT, we inject currents into a subject using multiple electrodes and measure boundary voltages to reconstruct a cross-sectional image of internal resistivity distribution. We found that a simplified, therefore fast, version of the impedance imaging method can be used for detection and monitoring of apnea and edema. We have showed the feasibility of this method through computer simulations and human experiments. We speculate that the EIT imaging technique will be more reliable than the current impedance apnea monitoring method, since we are monitoring the change of internal lung resistivity. However, more study is required to verify that this method performs better in the presence of motion artifact than the conventional two-electrode impedance apnea monitoring method. Future work should include experiments which carefully simulate different kinds of motion artifacts.

An electrical impedance tomography (EIT) system that uses the optimal current method to inject currents and the regularized Newton-Raphson algorithm to reconstruct an image of resistivity distribution is discussed. Iterative methods to derive the optimal current patterns through iterative physical measurements are developed. Direct methods to first determine the resistance matrix of a resistivity distribution through a set of current bases is injected and the measured voltage responses are stored. This permits iterative reconstruction techniques to operate on the stored data without requiring lengthy data taking from the object and reduces the effects of motion artifacts. The direct methods have superior performance as compared to the iterative methods in both optimal current and voltage generation. The results obtained with three sets of current bases are studied. >

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. >