ORCID Identifier(s)

0000-0002-2755-5386

Graduation Semester and Year

Fall 2024

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Aerospace Engineering

Department

Mechanical and Aerospace Engineering

First Advisor

Ashfaq Adnan

Second Advisor

Kamesh Subbarao

Third Advisor

Robert M Taylor

Fourth Advisor

Md Rassel Raihan

Fifth Advisor

Shuchisnigdha Deb

Abstract

Understanding brain health in an accelerative environment using integrated signal analysis, phantom head tissue manufacturing, and Electroencephalography (EEG). Traumatic Brain Injury (TBI) is considered a ‘silent epidemic’ because of its high incidence and disability risks. In the aerospace scenario, sudden and severe turbulence can cause occupants of an aircraft to lose balance and fall, leading to head injuries. Objects in the cabin or overhead bins can act as projectiles. High altitude-induced hypoxemia may cause an inflammatory response in the brain and amplify the severity risk of TBI. Electrophysiological abnormalities from TBI can be visible in EEG. EEG is used to sense and localize the brain's neural activities. Here, a synthetically generated brain-like signal is passed through a newly designed phantom head tissue and sensed by conventional EEG systems. The goal is to develop a methodology to uncouple EEG signals from motion-induced signals and accurately detect the location of potentially injured regions inside brain tissue. The study's first phase involves the development of a source localization algorithm for EEG using a combined experiment and simulation to enable more accuracy than the degree of accuracy available in commercial EEG systems. This algorithm has been evaluated using a 32-channel-wet EEG electrode setup. Our second phase focused on advancing the technologies by applying EEG to realistic phantom heads. A real human head tissue comprises several layers. Polydimethylsiloxane (PDMS)-Carbon fiber (CF) composites were chosen to produce a multilayer head phantom model. The results were subsequently compared with the statistical analyses of 56 prior experimental datasets concerning various head tissue layers. Finally, a phantom head is manufactured. Mobile EEG and industrial-grade robotic arms have been used to mimic different dynamic motions and conduct experiments in a dynamic environment. An algorithm is developed to uncouple unwanted motion artifacts and environmental noises. The algorithm has been tested and compared with commercial methods.

Keywords

Brain Signal, EEG, Source Localization, Electrical Conductivity, Composite Material, PDMS, Carbon Fiber, Phantom Head, Pre-Processing Pipeline, Dynamic Testing With EEG, Dynamic Decoupling

Disciplines

Aerospace Engineering | Biology and Biomimetic Materials | Biomedical Engineering and Bioengineering | Signal Processing | Structures and Materials

License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Comments

I express my gratitude to Dr. Ashfaq Adnan for his support, guidance, and support throughout the development of this thesis. I am grateful to Dr. Kamesh Subbarao for supporting us with advice and insights on developing the source localization algorithm. I thank Dr. Suchisnigdha Deb and Dr. Md Rassel Raihan for facilitating their lab at The University of Texas at Arlington (UTA) and the University of Texas at Arlington Research Institute (UTARI) lab. Finally, I thank my supervising committee for their insightful feedback that helped shape my research. This work was supported by a grant from the Office of Naval Research (ONR)’s Force Health Protection (FHP) program (through the Award # ONR: N00014-21-1-2051: Dr. Timothy Bentley, (Program Manager)

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