Compensation of Contact Impedance Variation for Cerebral Electrical Impedance Tomography

Abstract

Electrical impedance tomography (EIT) is a promising technique for conductivity distribution reconstruction. Considering the fact that cerebral disease causes variation of conductivity distribution, EIT technique can be used to reflect the pathological change in the cerebral region. This would offer an alternative for the timely diagnosis and treatment of cerebral disease. In cerebral EIT, contact impedance between the electrode and the scalp changes with time, which largely affects the reconstruction quality. To conquer this problem, a compensation method is proposed for voltage data correction when contact impedance varies. By analysis of boundary measurement, the electrode with contact impedance variation and how much contact impedance changes are determined. Together with a prior matrix, voltage data in the case of contact impedance variation can be compensated. Reconstruction of conductivity distribution is implemented by the L1 regularization method. The performance of the proposed method is evaluated under contact impedance variation of a single electrode, a pair of electrodes, and 16 electrodes. In addition, the influence of noise with a signal-to-noise ratio of 40 dB is studied. The results show that the proposed method can effectively suppress the effect of contact impedance change on image quality. Even under the impact of noise, reconstructed images show great improvement. With this method, it is able to monitor cerebral disease in the clinical application of EIT where contact impedance variation is inevitable.