Fatoorechi,_Mohsen.pdf (34.88 MB)
Electroencephalogram signal acquisition in unshielded noisy environment
thesis
posted on 2023-06-08, 21:18 authored by Mohsen FatoorechiResearchers have used electroencephalography (EEG) as a window into the activities of the brain. High temporal resolution coupled with relatively low cost compares favourably to other neuroimaging techniques such as magnetoencephalography (MEG). For many years silver metal electrodes have been used for non-invasive monitoring electrical activities of the brain. Although these electrodes provide a reliable method for recording EEG they suffer from noise, such as offset potentials and drifts, and usability issues, e.g. skin prepa- ration and short circuiting of adjacent electrodes due to gel running. Low frequency noise performance is the key indicator in determining the signal to noise ratio of an EEG sensor. In order to tackle these issues a prototype Electric Potential Sensor (EPS) device based on an auto-zero operational amplifier has been developed and evaluated. The absence of 1/f noise in these devices makes them ideal for use with signal frequencies ~10Hz or less. The EPS is a novel active electrode electric potential sensor with ultrahigh input impedance. The active electrodes are designed to be physically and electrically robust and chemically and biochemically inert. They are electrically insulated (anodized) and scalable. These sensors are designed to be immersed in alcohol for sterilization purposes. A comprehensive study was undertaken to compare the results of EEG signals recorded by the EPS with different commercial systems. These studies comprised measurements of both free running EEG and Event Related Potentials. Strictly comparable signals were observed with cross correlations of higher than 0.9 between the EPS and other systems.
History
File Version
- Published version
Pages
153.0Department affiliated with
- Engineering and Design Theses
Qualification level
- doctoral
Qualification name
- phd
Language
- eng
Institution
University of SussexFull text available
- Yes
Legacy Posted Date
2015-07-28Usage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC