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The apparent resistance of a finite-thickness layer measured with a four-electrode plunge probe depends on the electrode insertion depth, electrode spacing, and layer thickness, as well as the resistivity ratio of an underlying layer. A physical model consisting of air, a saline solution layer, and an agar layer simulates the real situation of resistivity measurement. The saline layer represents the finite-thickness layer whose resistivity is to be measured by a plunge electrode probe, and the agar layer represents an underlying perturbing layer. A micropositioner controls the insertion depth of the four electrodes into the saline solution. With the apparent resistance measured on a semi-infinite-thickness layer of saline solution as standard, measurement results show decreasing apparent resistance and increasing error with increasing electrode insertion depth. This information is important for correct measurement of myocardial resistivity in vivo and in vitro.

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. >