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Dissertations / Theses on the topic 'EEGs (electroencephalograph)'

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Published: 3 June 2025

Last updated: 31 July 2025

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1

Ascolani, Gianluca. "EEG, Alpha Waves and Coherence." Thesis, University of North Texas, 2010. https://digital.library.unt.edu/ark:/67531/metadc28389/.

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This thesis addresses some theoretical issues generated by the results of recent analysis of EEG time series proving the brain dynamics are driven by abrupt changes making them depart from the ordinary Poisson condition. These changes are renewal, unpredictable and non-ergodic. We refer to them as crucial events. How is it possible that this form of randomness be compatible with the generation of waves, for instance alpha waves, whose observation seems to suggest the opposite view the brain is characterized by surprisingly extended coherence? To shed light into this apparently irretrievable co

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2

Huang, Dandan. "Electroencephalography (EEG)-based brain computer interfaces for rehabilitation." VCU Scholars Compass, 2012. http://scholarscompass.vcu.edu/etd/2761.

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Objective: Brain-computer interface (BCI) technologies have been the subject of study for the past decades to help restore functions for people with severe motor disabilities and to improve their quality of life. BCI research can be generally categorized by control signals (invasive/non-invasive) or applications (e.g. neuroprosthetics/brain-actuated wheelchairs), and efforts have been devoted to better understand the characteristics and possible uses of brain signals. The purpose of this research is to explore the feasibility of a non-invasive BCI system with the combination of unique sensorim

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Koppikar, Samir Dilip. "Privacy Preserving EEG-based Authentication Using Perceptual Hashing." Thesis, University of North Texas, 2016. https://digital.library.unt.edu/ark:/67531/metadc955127/.

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The use of electroencephalogram (EEG), an electrophysiological monitoring method for recording the brain activity, for authentication has attracted the interest of researchers for over a decade. In addition to exhibiting qualities of biometric-based authentication, they are revocable, impossible to mimic, and resistant to coercion attacks. However, EEG signals carry a wealth of information about an individual and can reveal private information about the user. This brings significant privacy issues to EEG-based authentication systems as they have access to raw EEG signals. This thesis proposes

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4

Sellergren, Albin, Tobias Andersson, and Jonathan Toft. "Signal processing through electroencephalography : Independent project in electrical engineering." Thesis, Uppsala universitet, Elektricitetslära, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-298771.

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This report is about a project where electroencephalography (EEG) wasused to control a two player game. The signals from the EEG-electrodeswere amplified, filtered and processed. Then the signals from the playerswere compared and an algorithm decided what would happen in the gamedepending on which signal was largest. The controls and the gaming mechanismworked as intended, however it was not possible to gather a signal fromthe brain with the method used in this project. So ultimately the goal wasnot reached.<br>electroencephalography, EEG

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5

Liu, Hui. "Online automatic epileptic seizure detection from electroencephalogram (EEG)." [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0012941.

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6

Tcheslavski, Gleb V. "Coherence and Phase Synchrony Analysis of Electroencephalogram." Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/30186.

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Phase Synchrony (PS) and coherence analyses of stochastic time series - tools to discover brain tissue pathways traveled by electrical signals - are considered for the specific purpose of processing of the electroencephalogram (EEG). We propose the Phase Synchrony Processor (PSP), as a tool for implementing phase synchrony analysis, and examine its properties on the basis of known signals. Long observation times and wide filter bandwidths can decrease bias in PS estimates. The value of PS is affected by the difference in frequency of the sequences being analyzed and can be related to that freq

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7

Lee, Pamela Wen-Hsin. "Mutual information derived functional connectivity of the electroencephalogram (EEG)." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/219.

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Monitoring the functional connectivity between brain networks is becoming increasingly important in elucidating brain functionality in normal and disease states. Current methods of detecting networks in the recorded EEG such as correlation and coherence are limited by the fact that they assume stationarity of the relationship between channels, and rely on linear dependencies. Here we utilize mutual information (MI) as the metric for determining nonlinear statistical dependencies between electroencephalographic (EEG) channels. Previous work investigating MI between EEG channels in subjects with

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8

Mathew, Blesy Anu. "ENTROPY OF ELECTROENCEPHALOGRAM (EEG) SIGNALS CHANGES WITH SLEEP STATE." UKnowledge, 2006. http://uknowledge.uky.edu/gradschool_theses/203.

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We hypothesized that temporal features of EEG are altered in sleep apnea subjects comparedto normal subjects. The initial aim was to develop a measure to discriminate sleep stages innormals. The longer-term goal was to apply these methods to identify differences in EEGactivity in sleep apnea subjects from normals. We analyzed the C3A2 EEG and anelectrooculogram (EOG) recorded from 9 normal adults awake and in rapid eye movement(REM) and non-REM sleep. The EEG signals were filtered to remove EOG contamination. Twomeasures of the irregularity of EEG signals, Sample Entropy (SpEn) and Tsallis Ent

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9

Bismark, Andrew W. "The Heritability Of And Genetic Contributions To, Frontal Electroencephalography." Diss., The University of Arizona, 2014. http://hdl.handle.net/10150/332852.

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The heritability of frontal EEG asymmetry, a potential endophenotype for depression, was investigated using a large set of adolescent and young adult twins. Additionally, the relationship between polymorphisms within three serotonin genes, two receptor genes and one transporter gene, and frontal EEG asymmetry was also investigated. Using Falconer's estimate, frontal EEG asymmetry was shown to be more heritable at lateral compared to medial cites across nearly all reference montages, and greater in males compared to females. Using structural equation modeling (SEM), and investigating both addit

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10

Boyle, Stephanie Claire. "Investigating the neural mechanisms underlying audio-visual perception using electroencephalography (EEG)." Thesis, University of Glasgow, 2018. http://theses.gla.ac.uk/8874/.

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Traditionally research into how we perceive our external world focused on the unisensory approach, examining how information is processed by one sense at a time. This produced a vast literature of results revealing how our brains process information from the different senses, from fields such as psychophysics, animal electrophysiology, and neuroimaging. However, we know from our own experiences that we use more than one sense at a time to understand our external world. Therefore to fully understand perception, we must understand not only how the brain processes information from individual sens

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11

Formaggio, E. "Integrating electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) in epilepsy." Doctoral thesis, Università degli studi di Padova, 2010. http://hdl.handle.net/11577/3426904.

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Introduction Combined electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) studies enables to non invasively investigate human brain function and to find the direct correlation of these two important measures of brain activity. The combination of these technologies provides informations and details on the spatio-temporal aspects of human brain processing. fMRI has an excellent spatial resolution and allows the localization of brain regions in which there is a change in the level of neuronal activity during an experimental condition compared to a control condition. In

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12

D'ROZARIO, Angela Louise. "Electroencephalogram (EEG) biomarkers of neurobehavioural dysfunction in obstructive sleep apnea." Thesis, The University of Sydney, 2014. http://hdl.handle.net/2123/9886.

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Obstructive sleep apnea (OSA) affects an estimated 2-4% of middle–aged adults yet we are still exploring how best to delineate the neurophysiological deficits that accompany this disorder. Untreated OSA leads to an increased risk of motor vehicle accidents. Traditional polysomnographic (PSG) metrics do not consistently correlate with daytime functioning. There is a clinical need for simple biomarkers to identify individuals susceptible to OSA-related cognitive deficits. There is a close relationship between EEG-based changes in brain activity and daytime function in healthy sleepers. No studi

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13

Barne, Louise Catheryne. "Electroencephalographic correlates of temporal learning." reponame:Repositório Institucional da UFABC, 2016.

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Orientador: Prof. Dr. André Mascioli Cravo<br>Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Neurociência e Cognição, 2016.<br>We constantly learn and update our predictions about when events we cause will occur. This flexibility is important to program motor actions and to estimate when errors have been made. However, the mechanisms that govern learning and updating in temporal domain are largely unknown. In order to clarify these mechanisms we had three mains objectives: 1. To describe how we learn a new temporal relation between two events and how expecta

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14

Gustafsson, Johan. "Finding potential electroencephalography parameters for identifying clinical depression." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-256392.

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This master thesis report describes signal processing parameters of electroencephalography (EEG) signals with a significant difference between the signals from the animal model of clinical depression and the non-depressed animal model. The signal from the depressed model had a weaker power in gamma (30 - 80 Hz) than the non-depressed model during awake and it had a stronger power in delta (1.5 - 4 Hz) during sleep. The report describes the process of using visualisation to understand the shape of the signal which helps with interpreting results and helps with the development of parameters. A g

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15

SAIBENE, AURORA. "A Flexible Pipeline for Electroencephalographic Signal Processing and Management." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2022. http://hdl.handle.net/10281/360550.

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L'elettroencefalogramma (EEG) fornisce registrazioni non-invasive delle attività e delle funzioni cerebrali sotto forma di serie temporali, a loro volta caratterizzate da una risoluzione temporale e spaziale (dipendente dai sensori), e da bande di frequenza specifiche per alcuni tipi di condizioni cerebrali. Tuttavia, i segnali EEG risultanti sono non-stazionari, cambiano nel tempo e sono eterogenei, essendo prodotti da differenti soggetti e venendo influenzati da specifici paradigmi sperimentali, condizioni ambientali e dispositivi. Inoltre, questi segnali sono facilmente soggetti a rumore e

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16

Simms, Lori A. Bodenhamer-Davis Eugenia. "Neuropsychologic correlates of a normal EEG variant the mu rhythym /." [Denton, Tex.] : University of North Texas, 2008. http://digital.library.unt.edu/permalink/meta-dc-9032.

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17

Birch, Gary Edward. "Single trial EEG signal analysis using outlier information." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/28626.

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The goal of this thesis work was to study the characteristics of the EEG signal and then, based on the insights gained from these studies, pursue an initial investigation into a processing method that would extract useful event related information from single trial EEG. The fundamental tool used to study the EEG signal characteristics was autoregressive modeling. Early investigations pointed to the need to employ robust techniques in both model parameter estimation and signal estimation applications. Pursuing robust techniques ultimately led to the development of a single trial processing meth

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18

Holt, Mark Rowan Gorton. "The use of neural networks in the analysis of the anaesthetic electroencephalogram." Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.390525.

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19

Gasparini, John M. "An Electroencephalographic (EEG) Study of Hypofrontality during Music Induced Flow Experiences." Thesis, Northcentral University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10830810.

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<p> Since Csikszentmihalyi identified the psychological experience of flow over 40 years ago, the experiences have been heralded as the optimum human function and prescriptive to high levels of well-being and quality of life. Csikszentmihalyi theorized that flow represented an autonomous reality that represented an altered state unlike any other human experience. Flow states emerged from intrinsically motivated behavior that represented a fragile balance between the level of enjoyment from novel task stimulation and a sense of self-efficacy required to meet the specific task demands. However,

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20

Witt, Tyler S. "A Modular, Wireless EEG Platform Design." University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406821524.

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21

Hajipour, Sardouie Sepideh. "Signal subspace identification for epileptic source localization from electroencephalographic data." Thesis, Rennes 1, 2014. http://www.theses.fr/2014REN1S185/document.

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Lorsque l'on enregistre l'activité cérébrale en électroencéphalographie (EEG) de surface, le signal d'intérêt est fréquemment bruité par des activités différentes provenant de différentes sources de bruit telles que l'activité musculaire. Le débruitage de l'EEG est donc une étape de pré-traitement important dans certaines applications, telles que la localisation de source. Dans cette thèse, nous proposons six méthodes permettant la suppression du bruit de signaux EEG dans le cas particulier des activités enregistrées chez les patients épileptiques soit en période intercritique (pointes) soit e

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22

Echauz, Javier R. "Wavelet neural networks for EEG modeling and classification." Diss., Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/15629.

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23

Lorensen, Tamara Dawn. "Defining anterior posterior dissociation patterns in electroencephalographic comodulation in Chronic Fatigue Syndrome and depression." Queensland University of Technology, 2004. http://eprints.qut.edu.au/16552/.

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This is a study of quantitative electroencephalographic (QEEG) comodulation analysis, which is used to assist in identifying regional brain patterns associated with Chronic Fatigue Syndrome (CFS) compared to an EEG normative database. Further, this study investigates EEG patterns in depression which is found to be a highly comorbid condition to CFS. The QEEG comodulation analysis examines spatial-temporal cross-correlation of spectral estimates in the individual resting dominant frequency band. A pattern shown by Sterman and Kaiser (2001) and referred to as the Anterior Posterior Dissociati

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24

Duta, Mihaela D. "The study of vigilance using neural networks analysis of EEG." Thesis, University of Oxford, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.301454.

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25

Heath, Jacob. "Biometric Classification of Human Subjects Using Electroencephalography Auditory Event-Related Potentials." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439300974.

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26

Harris, Charissa Rosalynde. "Evaluation of electroencephalography as an objective measure of pain and analgesia in sheep." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/25711.

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Australian sheep routinely undergo surgical procedures without pain relief for castration, tail docking and mulesing. Electroencephalography (EEG) measures pain in livestock by comparing pre- and post-surgical states. This thesis aimed to assess EEG as an objective measure of pain and analgesic efficacy in sheep undergoing surgical procedures in a commercial farm setting. EEG output of anaesthetised lambs was compared to conscious lambs undergoing castration. Significant changes were found in conscious lambs between lignocaine treated and untreated lambs from pre- to post-castration. A pilo

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27

Zamora, Mayela E. "The study of the sleep and vigilance electroencephalogram using neural network methods." Thesis, University of Oxford, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365699.

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28

Al-Nashi, Hamid Rasheed. "A maximum likelihood method to estimate EEG evoked potentials /." Thesis, McGill University, 1985. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=72016.

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A new method for the estimation of the EEG evoked potential (EP) is presented in this thesis. This method is based on a new model of the EEG response which is assumed to be the sum of the EP and independent correlated Gaussian noise representing the spontaneous EEG activity. The EP is assumed to vary in both shape and latency, with the shape variation represented by correlated Gaussian noise which is modulated by the EP. The latency of the EP is also assumed to vary over the ensemble of responses in a random manner governed by some unspecified probability density. No assumption on stationarity

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29

Lahr, Jacob [Verfasser], and Andreas [Akademischer Betreuer] Schulze-Bonhage. "Electromyographic signals in intracranial electroencephalographic recordings = Elektromyographische Signale in intrakraniellen EEG-Aufnahmen." Freiburg : Universität, 2012. http://d-nb.info/1123473927/34.

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30

ATTARD, TREVISAN ADRIAN. "NOVEL COMPUTATIONAL ELECTROENCEPHALOGRAPHIC (EEG) METHODOLOGIES FOR AUTISM MANAGEMENT AND EPILEPTIC SEIZURE PREDICTION." Doctoral thesis, Università degli Studi di Milano, 2015. http://hdl.handle.net/2434/333759.

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The doctoral thesis deals with a novel methodology of looking and processing electroencephalographic (EEG) data. The first part deals with real-time brain stimulation in the form of a sonified neurofeedback therapy derived from a clinically comparable portable, 4-channel EEG system. The therapy aims to provide an effective management for symptoms of the Autism Spectrum Disorder (ASD). ASD is characterized with a high level of delta electroencephalographic waveform levels, while alpha and beta prove to be present at lower levels especially in the frontal-temporal regions. The treatment aims at

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31

Rennie, Christopher John. "Modeling the large-scale electrical activity of the brain." Thesis, The University of Sydney, 2001. http://hdl.handle.net/2123/816.

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Modeling of brain activity is often seen as requiring great computing power. However in the special case of modeling scalp EEG it is possible to adopt a continuum approximation for the cortex, and then to use the techniques of wave physics to describe its consequent large-scale dynamics. The model incorporates the following critical components: two classes of neurons (excitatory and inhibitory), the typical number and strength of connections between these two classes, the corresponding connections within the thalamus and between the thalamus and cortex, the time constants and basic physio

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32

Riddington, Edward Peter. "Automated interpretation of the background EEG using fuzzy logic." Thesis, University of Plymouth, 1998. http://hdl.handle.net/10026.1/1109.

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A new framework is described for managing uncertainty and for dealing with artefact corruption to introduce objectivity in the interpretation of the electroencephalogram (EEG). Conventionally, EEG interpretation is time consuming and subjective, and is known to show significant inter- and intra-personnel variation. A need thus exists to automate the interpretation of the EEG to provide a more consistent and efficient assessment. However, automated analysis of EEGs by computers is complicated by two major factors. The difficulty of adequately capturing in machine form, the skills and subjective

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33

Gabran, Salam. "Design and Optimization Methodology of Sub-dermal Electroencephalography Dry Spike-Array Electrode." Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/2793.

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Monitoring bio-electric events is a common procedure, which provides medical data required in clinical and research applications. Electrophysiological measurements are applied in diagnosis as well as evaluation of the performance of different body organs and systems, e. g. the heart, muscles and the nervous system. Furthermore, it is staple feature in operation rooms and extensive care units. The performance of the recording system is affected by the tools and instrumentation used and the bio-electrode is a key-player in electrophysiology, hence, the improvements in the electrode

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34

Nagabushan, Naresh. "Analyzing and Classifying Neural Dynamics from Intracranial Electroencephalography Signals in Brain-Computer Interface Applications." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/90183.

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Brain-Computer Interfaces (BCIs) that rely on motor imagery currently allow subjects to control quad-copters, robotic arms, and computer cursors. Recent advancements have been made possible because of breakthroughs in fields such as electrical engineering, computer science, and neuroscience. Currently, most real-time BCIs use hand-crafted feature extractors, feature selectors, and classification algorithms. In this work, we explore the different classification algorithms currently used in electroencephalographic (EEG) signal classification and assess their performance on intracranial EEG (iEEG

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35

ROHON, MARIE-ANGE. "Eeg dans la surveillance per-operatoire lors des restaurations carotidiennes." Aix-Marseille 2, 1988. http://www.theses.fr/1988AIX20086.

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36

Lipoth, Leon L. 1964. "Neural network based detection of EEG abnormalities." Ottawa, 1991.

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37

Gibson, Christopher. "Joint time-frequency analysis and filtering of single trial event-related potentials." Thesis, Sheffield Hallam University, 2000. http://shura.shu.ac.uk/19686/.

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The ongoing electrical activity of the brain is known as the electroencephalograph (EEG). Event related potentials (ERPs) are voltage deviations in the EEG elicited in association with stimuli. Their elicitation require cognitive processes such as response to a recognised stimulus. ERPs therefore provide clinical information by allowing an insight into neurological processes. The amplitude of an event-related potential is typically several times less than the background EEG. The background EEG has the effect of obscuring the ERP and therefore appropriate signal processing is required for its r

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Rasheed, S. "RECOGNITION OF PRIMARY COLOURS IN ELECTROENCEPHALOGRAPH SIGNALS USING SUPPORT VECTOR MACHINES." Doctoral thesis, Università degli Studi di Milano, 2011. http://hdl.handle.net/2434/155486.

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In this study we have worked on the classification of EEG signals produced by the exposure of primary colours (RGB). The main goal of this study was to perform an offline analysis and classification of color information obtained from EEG signals recorded in response to individual RGB colours presentation in order to verify our hypothesis, if the observation of different colors can be detected or not by selecting different frequency bands. We have also performed an offline analysis of EEG signals produced by the colour imagination to observe similarities in EEG signals between actual color expo

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Monnin, Jason. "A VALIDATION OF A PROTOTYPE DRY ELECTRODE SYSTEM FOR ELECTROENCEPHALOGRAPHY." Wright State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=wright1316771492.

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40

Löfhede, Johan. "Classification of Burst and Suppression in the Neonatal EEG." Licentiate thesis, Högskolan i Borås, Institutionen Ingenjörshögskolan, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-3448.

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The brain requires a continuous supply of oxygen and even a short period ofreduced oxygen supply risks severe and lifelong consequences for theaffected individual. The delivery is a vulnerable period for a baby who mayexperience for example hypoxia (lack of oxygen) that can damage the brain.Babies who experience problems are placed in an intensive care unit wheretheir vital signs are monitored, but there is no reliable way to monitor thebrain directly. Monitoring the brain would provide valuable informationabout the processes going on in it and could influence the treatment and helpto improve

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Murrell, Joanna. "Spontaneous EEG changes in the equine surgical patient." Thesis, University of Bristol, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340352.

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Girão, Leonor Lopes Ribeiro da Silva. "Neural correlations during brain activation in arithmetical tasks – an approach using electroencephalographic data." Master's thesis, Faculdade de Ciências e Tecnologia, 2010. http://hdl.handle.net/10362/4257.

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Dissertação apresentada na Faculdade de Ciências e Tecnologiea da Universidade Nova de Lisboa, para obtenção do Grau de Mestre em Engenharia Biomédica<br>The present study aims at examining the correlation among different brain areas while the subjects performed an arithmetical task, and how these differ from the mental relations in the same subjects during a resting state. In order to this, both linear and nonlinear methods were used, i.e., both algorithms capable of detecting linear relations and algorithms capable of detecting correlations without assuming any type of parametric relationshi

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Szafir, Daniel J. "Non-Invasive BCI through EEG." Thesis, Boston College, 2010. http://hdl.handle.net/2345/1208.

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Thesis advisor: Robert Signorile<br>It has long been known that as neurons fire within the brain they produce measurable electrical activity. Electroencephalography (EEG) is the measurement and recording of these electrical signals using sensors arrayed across the scalp. Though there is copious research in using EEG technology in the fields of neuroscience and cognitive psychology, it is only recently that the possibility of utilizing EEG measurements as inputs in the control of computers has emerged. The idea of Brain-Computer Interfaces (BCIs) which allow the control of devices using brain s

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Mulyana, Ridwan S. "A Low Voltage, Low Power 4th Order Continuous-time Butterworth Filter for Electroencephalography Signal Recognition." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1281981810.

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Rissacher, Daniel J. "Neural network recognition of pain state in EEG recordings." Thesis, Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/16646.

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Pillain, Axelle. "Line, Surface, and Volume Integral Equations for the Electromagnetic Modelling of the Electroencephalography Forward Problem." Thesis, Télécom Bretagne, 2016. http://www.theses.fr/2016TELB0412/document.

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La reconstruction des sources de l'activité cérébrale à partir des mesures de potentiel fournies par un électroencéphalographie (EEG) nécessite de résoudre le problème connu sous le nom de « problème inverse de l'EEG ». La solution de ce problème dépend de la solution du « problème direct de l'EEG », qui fournit à partir de sources de courant connues, le potentiel mesuré au niveau des électrodes. Pour des modèles de tête réels, ce problème ne peut être résolut que de manière numérique. En particulier, les équations intégrales de surfaces requièrent uniquement la discrétisation des interfaces e

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Hill, Cynthia DeLeon. "The Effects Of The Allocation Of Attention Congruent With Lateralized Cognitive Tasks On EEG Coherence Measurements." Thesis, University of North Texas, 2002. https://digital.library.unt.edu/ark:/67531/metadc3140/.

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The single task condition of the Urbanczyk and Kennelly (1991) study was conducted while recording a continuous electroencephalographic (EEG) record. Attention was allocated by instructed lateral head orienting and eye gaze either congruently or incongruently with lateralized cognitive tasks. Thirty university subjects retained a digit span or a spatial location span for a 20 second retention interval. EEG data were extracted from the 20 second retention intervals and interhemispheric coherence was calculated for homologous sites in the temporal, parietal and occipital regions of the brain. Th

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KPENOU, LEONTINE. "Electroencephalogramme quantifie : cartographie eeg et test au clorazepate dipotassique." Montpellier 1, 1989. http://www.theses.fr/1989MON11174.

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Vennelaganti, Swetha. "AGING AND SLEEP STAGE EFFECTS ON ENTROPY OF ELECTROENCEPHALOGRAM SIGNALS." UKnowledge, 2008. http://uknowledge.uky.edu/gradschool_theses/553.

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The aging brain is characterized by alteration in synaptic contacts, which leads to decline of motor and cognitive functions. These changes are reflected in the age related shifts in power spectrum of electroencephalogram (EEG) signals in both wakefulness and sleep. Various non-linear measures have been used to obtain more insights from EEG analysis compared to the conventional spectral analysis. In our study we used Sample Entropy to quantify regularity of the EEG signal. Because elderly subjects arouse from sleep more often than younger subjects, we hypothesized that Entropy of EEG signals f

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Thomas, Cameron W. "Altering time compression algorithms of amplitude-integrated electroencephalography display improves neonatal seizure detection." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1367926003.

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