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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. >

Static image reconstruction in electrical impedance tomopphy (EIT) using iterative algorithms requires a large computation time. We developed an improved NewtonRaphson (N-R) method which is more efficient, robust, and easily parallelizable. In order to check the feasibility of parallel computation in EIT, we implemented the algorithm on a parallel computer system. The results show a reduction in the computation time within a certain hiit as we increase the number of processors. We conclude that the improved N-R method is highly parallelizable and the use of parallel computers such as Transputers may solve the computational problems in static impedance imaging.

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. >

A 32-electrode, 12-bit electrical impedance tomograph (EIT) which is capable of injecting optimal patterns of currents into an object to achieve maximum distinguishability is presented. The software for the system is described, and static images reconstructed from a circular 2-D phantom are shown. The EIT software consists of four parts: the interactive graphical finite-element mesh generator; the sparse linear system equation solver including node renumbering schemes; the calculation of the optimal patterns of injection current and the implementations of the EIT image reconstruction algorithms; and image display and postprocessing. >

An investigation has been made of multiple-electrode system to monitor the impedance changes corresponding to volume changes of the urinary bladder, using a finite-element model of the human body. The authors used an adaptive method for determining the optimal currents which would provide maximal impedance changes. They present simulation results and discuss the relationships between impedance change and the number and placement of the electrodes. >