Dynamic electrical impedance tomography image reconstruction of neonate lung function based on linear Kalman filter techniques

Electrical impedance Tomography (EIT) has great potential as a low cost continuous monitoring system for neonate lung function. However EIT data obtained from clinical measurements are inherently noisy and require reconstruction algorithms that are robust enough to cope with these difficulties. In this paper, we examine the potential of a linear Kalman approach for EIT difference imaging. Simulated data is used for the reconstruction process; real time-data is being tested and the results will be introduced at a latter stage of this research. Our objective is to use this initial research to develop a nonlinear Kalman filter for frequency difference imaging of neonate lung function