Electrical impedance tomography reconstruction algorithm using extended Kalman filter

In electrical impedance tomography (EIT), the internal resistivity distribution of the unknown object is estimated using the boundary voltage data induced by different current patterns using various reconstruction algorithms. This paper presents a reconstruction algorithm based modified extended Kalman filter technique that is able to track fast change in the impedance distribution. The computer simulation for the 32 channels synthetic data shows that the reconstruction performance of the proposed scheme is improved compared to that of the conventional Kalman filter algorithm at the expense of slightly increased computational burden.