Electrical Impedance Tomography/Spectroscopy (EITS): a Code Division Multiplexed (CDM) approach

Electrical Impedance Tomography and Spectroscopy (EITS) is a noninvasive imaging technique that creates images of cross-sections "tomos" of objects by discriminating them based on their electrical impedance. This thesis investigated and successfully confirmed the use of Code Division Multiplexing (CDM) using Gold codes in Electrical Impedance Tomography and Spectroscopy. The results obtained showed 3.5% and 6.2% errors in determining the position and size of imaged anomalies respectively, with attainable imaging speed of 462 frames/second. These results are better, compared to those reported when using Time Division Multiplexing (TDM) and Frequency Division Multiplexing (FDM).This new approach provides a more robust mode of EITS for fast changing dynamic systems by eliminating temporal data inconsistencies. Furthermore, it enables robust use of frequency difference imaging and spectroscopy in EITS by eliminating frequency data inconsistencies. In this method of imaging, electric current patterns are safely injected into the imaged object by a set of electrodes arranged in a single plane on the objects surface, for 2-Dimensional (2D) imaging. For 3-Dimensional (3D) imaging, more electrode planes are used on the objects surface. The injected currents result in measurable voltages on the objects surface. Such voltages are measured, and together with the input currents, and a Finite Element Model (FEM) of the object, used to reconstruct an impedance image of the cross-sectional contents of the imaged object. The reconstruction process involves the numerical solutions of the forward problem; using Finite Element solvers and the resulting ill-posed inverse problem using iterative Optimization or Computational Intelligence methods. This method has applications mainly in the Biomedical imaging and Process monitoring fields. The primary interests of the author are, in imaging and diagnosis of cancer, neonatal pneumonia and neurological disorders which are leading causes of death in Africa and world-wide.

Grantor dc:publisher.institution

Department of Electrical Engineering

Year dc:date.issued

2016

Author dc:creator

• Tšoeu, Mohohlo Samuel

Advisor dc:contributor.advisor

• Inggs, Michael

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/11427/22866

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/22866