Date of Award

5-2021

Culminating Project Type

Thesis

Degree Name

Electrical Engineering: M.S.

Department

Electrical Engineering

College

College of Liberal Arts

First Advisor

Dr. Yi Zheng

Second Advisor

Dr. Mahbub Hossain

Third Advisor

Dr. Shensheng Tang

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Keywords and Subject Headings

EIT, FPGA, Zynq, C#, Low Frequency

Abstract

Electrical Impedance Tomography (EIT) is an imaging technique which is noninvasive and uses the internal conductivity distribution of the object of interest to form a tomographic image. It is performed by applying electrodes to the surface of the object. An alternating current up to frequency 10kHz is applied through a pair of electrodes, and the induced voltage is measured on other electrodes. These current and voltage values are used to reconstruct the internal conductivity distribution. The EIT imaging is increasingly getting used in clinical applications, as it is safer, portable, and low cost if compared with available imaging technologies used in clinical settings.

The goal of this project is to develop a low frequency Zynq SoC-based EIT system. A Zynq 7020 device-based development board, Zedboard, interfaced with a customized hardware circuit, is used to develop a complete EIT system. A graphical user interface is developed using C# Graphic User Interface (GUI) application to control the hardware and visualize the results. It is a twelve-electrode system, and current injection and voltage measurement is performed through Zynq SoC. There are two image reconstruction algorithms developed, Gauss Newton One Step and Total variation. The algorithms are implemented in Zynq SoC using software-hardware co-design. The algorithms are also implemented in C#. The image reconstruction performance between the two algorithms is compared. The computation performance between Zynq SoC implementation and C# implementation is also compared to understand the feasibility of FPGA implementation of EIT image reconstruction algorithms.

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