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Electrical impedance tomography (EIT) is a medical imaging technique in which an image of the conductivity or permittivity of part of the body is inferred from surface electrical measurements. Mathematically, the problem of recovering conductivity from surface measurements of current and potential is a non-linear inverse problem and is severely ill-posed. In this paper, we propose a novelty algorithm which based on Nachman theory. The algorithm is validated by numerical simulations of a domain with fixed resistively and by experimental data collected from the boundary of a human chest during normal breathing. The experiment result shows that the algorithm takes the advantage of speed and accurate.