Electrical Impedance Tomography (EIT)

Interested readers about Electrical Impedance Tomography (EIT) will found my thesis here:
www.gaggero.ch/thesis

Abstract:

Electrical Impedance Tomography (EIT) calculates an image of the conductivity distribution within a body from electrical stimulation and measurements at the body surface. This work develops advances in signal acquisition hardware, optimization of stimulation patterns, and analysis of detection limits for EIT. The EIT data acquisition and image reconstruction process is systematically analyzed with respect to the influence of noise and other measurement deficiencies on image quality. A complete EIT system with 32 active electrodes has been developed, with which the theoretical predictions could be verified and practical applications could be studied.

The novel concept of distinguishability is developed for a theoretical analysis of EIT system performance. It measures the likelihood that the measured differential EIT signal is generated by actual impedance changes and not by random fluctuations. This distinguishability criterion can be considered as a signal-to-noise ratio, and it serves as a valuable benchmark to assess the performance of EIT systems. Using numerical simulations, we have studied the optimum signal acquisition strategy for differential EIT signals, in order to maximize image quality. The most favorable angles between injecting and sinking electrode are found in the range from 60 to 150 degrees. We have also studied, theoretically as well as experimentally, the miniaturization limits of EIT systems. It is concluded that EIT system miniaturization is essentially determined by the Joule heating effect and the cooling rate of the sample volume. When scaling EIT systems up to very large dimensions, electronic noise on the sample (current injection and voltage measurements) finally limits the distinguishability in reconstructed EIT images.

A prototype of the developed hardware architecture was realized and proof-of-concept studies were carried out using both thoracic-EIT and the micro-EIT setups. As a major application of the work carried out in this thesis, we have demonstrated the capability of the developed EIT system to serve as a cost-effective real-time monitor for the reliable monitoring of the ventilation and cardiac related impedance changes on patients. The advances presented in this work can help build the capability of EIT to monitor and optimize mechanical ventilation of patients in intensive care units, which has the potential of enabling safer, automatic ventilation strategies, possibly preventing the unnecessary death of tens of thousands of patients every year.

enjoy!

Pascal