Electrical impedance tomography using the extended Kalman filter.
In this paper, we propose an algorithm that, using the extended Kalman filter, solves the inverse problem of estimating the conductivity/resistivity distribution in electrical impedance tomography (EIT). The algorithm estimates conductivity/resistivity in a wide range. The purpose of this investigation is to provide information for setting and controlling air volume and pressure delivered to patients under artificial ventilation. We show that, when the standard deviation of the measurement noise level raises up to 5% of the maximal measured voltage, the conductivity estimates converge to the expected vector within 7% accuracy of the maximal conductivity value, under numerical simulations, with spatial a priori information. A two-phase identification procedure is proposed. A cylindrical phantom with saline solution is used for experimental evaluation. An abrupt modification on the resistivity distribution of this solution is caused by the immersion of a glass object. Estimates of electrode contact impedances and images of the glass object are presented.
Trigo
Flávio Celso
FC
Department of Mechanical Engineering, Polytechnic School, University of São Paulo-SP, R. da Consolação 3064-171A, 01416-000 São Paulo, Brazil. ftrigo@netpoint.com.br
Gonzalez-Lima
Raul
R
Amato
Marcelo Brito Passos
MB
D000465:Algorithms; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D008168:Lung / Q000503:physiopathology; D008954:Models, Biological; D019047:Phantoms, Imaging; D010992:Plethysmography, Impedance / Q000295:instrumentation / Q000379:methods*; D001261:Pulmonary Atelectasis / Q000175:diagnosis / Q000503:physiopathology; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013909:Thorax / Q000502:physiology / Q000503:physiopathology