In electrical impedance tomography (EIT) an approximation for the internal
resistivity distribution is computed based on the knowledge of the injected
currents and measured voltages on the surface of the body. In some applica
tions the resistivity changes may be so fast that the information on the ti
me evolution of the resistivity distribution is either lost or severely blu
rred. In this paper we study with phantom experiments the capabilities of t
he earlier proposed approaches, Kalman filter and Kalman smoother. We show
that in "two-dimensional" phantom these approaches are capable of reconstru
cting a sequence of absolute images of a moving object, By an absolute imag
e we mean that no additional reference voltage measurement is needed for th
e image reconstruction. An image is obtained after each current injection.
Also, when compared to traditional reconstructions, the dynamic approaches
reveal much more information about the dynamic behaviour of the object.