Fernando Silva de Moura

Dynamic Imaging in Electrical Impedance Tomography of the Human Chest With Online Transition Matrix Identification

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.

The ACE1 thoracic Electrical Impedance Tomography system for ventilation and perfusion

Electrical Impedance Tomography (EIT) is a technique which can image the varying electrical properties of biological tissues. For clinical use of EIT, it can be advantageous to know both tissue conductivity and permittivity. Presented is the hardware design for the pairwise current injection active complex electrode (ACE1) EIT system which measures phasic voltages for conductivity and permittivity image reconstruction. In this system, alternating current is injected on electrodes on the boundary of a domain and single-ended voltage measurements are used in image reconstructions of the domains interior and in calculating the current applied at the electrodes.

Online transition matrix identification of the state evolution model for the extended Kalman filter in electrical impedance tomography

One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on contour electrical potential measurements caused by an imposed electrical current distribution into the boundary. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, it is observed poor tracking ability of the Extended Kalman Filter (EKF). An analytically developed evolution model is not feasible at this moment. The present work investigates the possibility of identifying the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model is identified using the history of resistivity distribution obtained by a sensitivity matrix based algorithm. To numerically identify the linear evolution model, it is used the Ibrahim Time Domain Method, normally used to identify the transition matrix on structural dynamics. The investigation was performed by numerical simulations of a time varying domain with the addition of noise. Numerical dificulties to compute the transition matrix were solved using a Tikhonov regularization. The EKF numerical simulations suggest that the tracking ability is significantly improved.

A proposal to monitor muscle contraction through the change of electrical impedance inside a muscle

Dynamically monitoring muscle contraction is an important task in sports training and rehabilitation programs. Internal muscles monitoring are specially challenging because they cannot be accessed by palpation or surface EMG. It is well known that blood flow through skeletal muscle can increase 15-to 25-fold during extreme exercise compared to its rest state. Additionally, at rest, some muscle capillaries have little or no blood flowing, but during strenuous exercise, all the capillaries open. With regard to electrical properties, blood resistivity is about half of muscle resistivity. Thus, global muscle resistivity have a tendency to change when it goes from rest to activity state. Recent results suggest that resistivity changes are related to contraction rate. Bearing that in mind, Electrical Impedance Tomography turns out to be an interesting signal to monitor muscle contraction by sensing resistivity changes related to muscle activity. If low intensity current is injected and electric potentials are measured through electrodes attached on skin, resistivity maps can be obtained using this data to solve an ill-posed inverse problem. In this work the electrical impedance was measured while a muscle was under repetitive contractions. Significant changes of electrical impedance were found in the frequency of contractions.

Interval Simulated Annealing applied to Electrical Impedance Tomography image reconstruction with fast objective function evaluation

The Electrical Impedance Tomography (EIT) reconstruction problem can be solved as an optimization problem in which the discrepancy between a simulated impedance domain and the observed one is minimized. This optimization problem can be solved by a combination of Simulated Annealing (SA) for optimization and the Finite Element Method (FEM) for simulating the impedance domain. A new objective function based on the total least squares error minimization is proposed. This objective function is ill-conditioned with dense meshes. Two possibilities to overcome ill-conditioning are considered: combination with another objective function (Euclidean distance) and inclusion of a regularization term. To speed up the algorithm, results from previous iterations are used to improve the present iteration convergence, and a preconditioner is proposed. This new reconstruction approach is evaluated with experimental data and compared with previous approaches.

Ultrasound study of hemodynamic changes by flow diverting stents in idealised and patient-specific anatomies

Whereas the use of flow diverter stents (FDs) represents a powerful treatment alternative to surgical clipping of intracranial aneurysms (IAs) presenting at arterial bifurcations, endovascular deployment of FDs often involves the jailing of daughter vessels (DV), and can affect the patency of the jailed DV.

Signal Processing Architecture for Electrical Tomography Impedance

This paper presents a description of an architecture of an EIT hardware for research. Both, hardware and software for capturing and processing of the EIT signals are addressed. The system is divided in modules with defined requirements and connections, therefore, different implementations are possible. Details of an implementation conceived to validate the architecture with respect to processing speed is also described.

Comparing two electrical impedance tomography algorithms: Gauss-Newton and topology optimization

Electrical Impedance Tomography (EIT) seeks to recover the impedance distribution within a body using boundary data. More specifically, given the measured potentials, the model of the body - an elliptic partial differential equation - and the boundary conditions, this technique solves a non-linear inverse problem for the unknown impedance. In this work, an algorithm called Topology Optimization Method (TOM) is applied to EIT and compared to the Gauss-Newton Method (GNM). The Topology Optimization has solved some non-linear inverse problems and some of its procedures were not investigated for EIT, for instance, the use of Sequential Linear Programming. Assuming a pure resistive medium, the static resistivity distribution of a phantom was estimated using a 2-D finite element model. While the first method (GNM) essentially solves several algebraic systems, the second (TOM) solves several linear programming problems. Results using experimental data are shown and the quality of the images obtained, time and memory used are compared for both algorithms. We intend to use these methods, in future works, for the visualization of a human lung subjected to mechanical ventilation.