Paper Info
Title
Dynamic Imaging in Electrical Impedance Tomography of the Human Chest With Online Transition Matrix Identification.
Abstract
One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.
Year
DOI
Venue
2010
10.1109/TBME.2009.2032529
IEEE Trans. Biomed. Engineering
Keywords
Field
DocType
transition matrix,expected value,time domain,impedance measurement,electrical resistivity,numerical analysis,electrical resistance,normal breathing,electric potential,electric resistance,extended kalman filter,newton raphson algorithm,conductivity,kalman filters,newton raphson,parameter estimation,numerical simulation,random walk,newton raphson method,tomography,kalman filter,electrical impedance tomography
Extended Kalman filter,Electrical resistance and conductance,Computer simulation,Computer science,Matrix (mathematics),Electronic engineering,Kalman filter,Estimation theory,Dynamic method,Electrical impedance tomography
Journal
Volume
Issue
ISSN
57
2
0018-9294
Citations 
PageRank 
References 
8
0.94
2
Authors
5
Name
Order
Citations
PageRank
Fernando Silva Moura1102.34
Julio Cesar Ceballos Aya280.94
Agenor Toledo Fleury380.94
Marcelo Britto Passos Amato4315.67
Raul Gonzalez Lima5398.39