Sensitivity Distribution Simulations of Impedance Tomography Electrode Combinations

As reconstruction techniques generating images in electrical impedance tomography (EIT) are sensitive to noise, small errors on measured data can result into large errors in final images. In order to optimize the signal acquisition from any region, measurement should possess highest sensitivity and selectivity in that region. This study was conducted to estimate measurement properties of various generally applied measurement schemes in EIT. Computer models were utilized in simulating the sensitivity distributions of neighboring, cross, opposite and adaptive methods. Highest sensitivities were obtained with the cross and opposite methods, whereas neighboring was the least sensitive, when investigating a single measurement. Maximum proportional selectivities in the centre of a 2D model were 100, 94, 88 and 62 %, respectively, as compared between the neighboring, cross, opposite and adaptive methods. In 3D, the corresponding values were 100, 55, 50 and 7.6 %. Adaptive method is flexible in current injection, yet trigonometric injection was used for simplicity, explaining the poor performance. Regions of negative sensitivity were detected, which may complicate the reconstruction. Nevertheless, studying sensitivity distributions may improve the outcome of EIT. In future, anatomically realistic models are utilized to derive measurements optimizing the sensitivity in the inner structures of the model.