The phenomenon of the increase in alpha EEG activity associated with eye closure has been shown to be successful for implementing environmental control for disabled persons. Studies in this thesis investigate strategies which improve the reliability, robustness, and ease of use of alpha EEG control systems. Primarily, research covers the effectiveness of alpha EEG detection algorithms (with regard to detection time and susceptibility to artifact) and the construction and use of EEG sensing electrodes. Many new techniques for the detection of the increase of alpha EEG associated with eye closure are researched, developed, implemented and evaluated. All detection techniques are compared to a conventional method using a novel performance parameterisation criterion. In conjunction with the application of the same EEG data sets to all techniques, the use of the performance criteria enables a fair and quantitative comparison to be made between alpha detection methodologies. Detection techniques employed include enhanced versions of conventional methods, localisation of apparent alpha sources in the brain, and preprocessing methods (such as spatial filtering, adaptive filtering and independent component analysis). The best performance of alpha EEG detection was given by the source power alpha localisation technique, which showed statistically significant and practically important improvements in performance over conventional techniques. Additionally, this localisation technique is convenient and fast to implement. In situations in which electrodes are intended for unsupervised use with environmental control systems, the evaluation of alternative electrode types to the conventional wet electrodes is required, as the use of wet electrodes has several drawbacks. The performance of wet, dry and insulating electrodes is compared in this research. One aspect of the quantitative comparison of electrodes types is the measurement of contact impedance. To enable the fast and accurate measurement of impedance spectra, a new impedance spectroscopy system was developed as part of this thesis. In addition to comparison of impedance criteria, electrodes were evaluated in the presence movement-based, and electric field induced, artifacts. The electrode comparisons were carried out in a direct and quantitative manner in a controlled test environment for the first time. Results indicate that, in contrast to earlier reports, both dry and insulating electrode perform well with respect to artifact and offer a viable alternative to wet electrodes for long-term monitoring of biosignals from the surface of the skin. More improvements are required before such electrodes are suitable for EEG usage.

The phenomenon of the increase in alpha EEG activity associated with eye closure has been shown to be successful for implementing environmental control for disabled persons. Studies in this thesis investigate strategies which improve the reliability, robustness, and ease of use of alpha EEG control systems. Primarily, research covers the effectiveness of alpha EEG detection algorithms (with regard to detection time and susceptibility to artifact) and the construction and use of EEG sensing electrodes. Many new techniques for the detection of the increase of alpha EEG associated with eye closure are researched, developed, implemented and evaluated. All detection techniques are compared to a conventional method using a novel performance parameterisation criterion. In conjunction with the application of the same EEG data sets to all techniques, the use of the performance criteria enables a fair and quantitative comparison to be made between alpha detection methodologies. Detection techniques employed include enhanced versions of conventional methods, localisation of apparent alpha sources in the brain, and preprocessing methods (such as spatial filtering, adaptive filtering and independent component analysis). The best performance of alpha EEG detection was given by the source power alpha localisation technique, which showed statistically significant and practically important improvements in performance over conventional techniques. Additionally, this localisation technique is convenient and fast to implement. In situations in which electrodes are intended for unsupervised use with environmental control systems, the evaluation of alternative electrode types to the conventional wet electrodes is required, as the use of wet electrodes has several drawbacks. The performance of wet, dry and insulating electrodes is compared in this research. One aspect of the quantitative comparison of electrodes types is the measurement of contact impedance. To enable the fast and accurate measurement of impedance spectra, a new impedance spectroscopy system was developed as part of this thesis. In addition to comparison of impedance criteria, electrodes were evaluated in the presence movement-based, and electric field induced, artifacts. The electrode comparisons were carried out in a direct and quantitative manner in a controlled test environment for the first time. Results indicate that, in contrast to earlier reports, both dry and insulating electrode perform well with respect to artifact and offer a viable alternative to wet electrodes for long-term monitoring of biosignals from the surface of the skin. More improvements are required before such electrodes are suitable for EEG usage.

This study proposes a series of 3 experiments to explore how the use of mental imagery affects expert vs. novice golfers differently, by comparing alpha and beta waves. In Experiment 1 experts and novices will putt under a pressure task or no pressure task. The researcher will analyze golfers’ putting success rate in addition to examining alpha and beta waves. Experiment 2 will expand upon the expected results of Experiment 1, focusing on experts’ and novices’ use of task-relevant and task-irrelevant mental imagery as pre-performance routines just before a putting task, with all conditions facing pressure. Finally, Experiment 3 will explore experts’ vs. novices’ use of task-relevant and task-irrelevant mental imagery the day before the pressure putting task. Researchers are expected to find increases in alpha wave activity to occur prior to the putting task in experts regardless of condition, which is consistent with the attention-arousal set theory’s concept of an optimal state of performance. Novices should display increases in alpha wave activity and reach their optimal state of performance when the type of mental imagery they use helps them relax, which should lead to a higher putting success rate.

Résumé : Au repos, l'activité du cerveau d'un humain sain est caractérisée par de larges fluctuations dans la bande de fréquences de 8-13 Hz d'un électroencéphalogramme (EEG), connue sous le nom de bande alpha. Bien qu'il soit établi que son activité varie d'un individu à l'autre, peu d'études se sont intéressées à la façon dont elle peut être reliée aux variations morphologiques des structures du cerveau. Entre autres, on pense que le corps géniculé latéral (CGL) et ses fibres efférentes (la radiation optique) jouent un rôle clé sur l'activité alpha, bien qu'il n'est pas certain que leur forme ou leur grosseur contribuent à sa variabilité inter-individuelle. Considérant l'utilisation courante d'EEG dans la recherche fondamentale ou clinique, ce sujet est important, mais difficile à traiter vu les problèmes associés à une bonne segmentation du CGL et de la radiation optique. Pour cette raison, nous avons utilisé la résonance magnétique de diffusion (IRMd), la résonance magnétique fonctionnelle (IRMf) et l'EEG sur 20 sujets sains pour mesurer la structure et la fonction, respectivement. L'analyse de la structure a nécessité une nouvelle approche semi-automatique pour segmenter le CGL et la radiation optique, qui nous a permis de mesurer plusieurs variables, telles que le volume et la position. Ces mesures correspondent bien aux connaissances sur la morphologie de ces structures basées sur des études post-mortem, et pourtant, nous avons trouvé que leur variabilité inter-sujet n'influençait pas la puissance des ondes alpha ou leur fréquence-type (p>0.05). Ces résultats suggèrent que la variabilité alpha soit médiée par d'autres sources structurelles. Notre méthodologie pourra servir pour de futures recherches sur l'influence de l'anatomie sur la fonction en IRMf, tomographie par émission de positron (TEP), EEG, etc., ou pour améliorer les recherches cliniques sur la radiation optique. / Abstract : At rest, healthy human brain activity is characterized by large electroencephalography (EEG) fluctuations in the 8-13 Hz range, commonly referred to as the alpha band. Although it is well known that EEG alpha activity varies across individuals, few studies have investigated how this may be related to underlying morphological variations in brain structure. Specifically, it is generally believed that the lateral geniculate nucleus (LGN) and its efferent fibres (optic radiation, OR) play a key role in alpha activity, yet it is unclear whether their shape or size variations contribute to its inter-subject variability. Given the widespread use of EEG alpha in basic and clinical research, addressing this is important, though difficult given the problems associated with reliably segmenting the LGN and OR. For this, we employed a multi-modal approach and combined diffusion magnetic resonance imaging (dMRI), functional magnetic resonance imaging (fMRI) and EEG in 20 healthy subjects to measure structure and function, respectively. For the former, we developed a new, semi-automated approach for segmenting the OR and LGN, from which we extracted several structural metrics such as volume, position and diffusivity. Although these measures corresponded well with known morphology based on previous post-mortem studies, we nonetheless found that their inter-subject variability was not significantly correlated to alpha power or peak frequency (p > 0.05). Our results therefore suggest that alpha variability may be mediated by an alternative structural source and our proposed methodology may in general help in better understanding the influence of anatomy on function.

This master‘s thesis presents the problems of EEG bio-feedback and its application for relaxing a person. It deals with the requirements of the sensing electrode and the biological signal amplifiers. The main substance of my thesis is the proposal of Alpha monitor, a device that uses the electrical activity of alpha brain waves for the realization of biological EEG feedback. The device concept takes into consideration the requirements of users’ security and also characteristics of alpha activity, which define the requirements for signal processing circuits and for propositions of the aural transducer. This master‘s thesis analyses given submission, proposes particular circuits, presents the overall electrical diagram and the list of components. The overall electrical diagram and single circuits are drawn within the EAGLE 5.7.0.

Indications are that autonomic under-arousal exists in children with ADHD. Published results are, however, controversial and few studies examine the relationship between the autonomic nervous system and focussed attention. In line with the indications of sympathetic under-arousal, patients with the disorder are treated with sympathomimetic stimulants such as Ritalin (methylphenidate). Since these medications stimulate the sympathetic nervous system, they possess the potential to influence cardiac function. The aims of this study were a) to assess autonomic nervous system functioning in 20 children with ADHD, as compared to controls, and to examine the effects of focussed attention and sympathomimetic medication on this system, b) to investigate cardiac functioning in 20 children with ADHD, as compared to controls, and to examine the effects of sympathomimetic medication on this system and c) to assess EEG functioning in children with ADHD, as compared to controls, and to examine the effects of sympathomimetic medication on this functioning. Children with ADHD were tested while they were stimulant-free and during a period in which they were on stimulant medication, while controls were tested once. Autonomic nervous system activity of the children was assessed at baseline and during focussed attention by means of heart rate variability (HRV) and skin conductivity. Attention was evoked by means of a program on the BioGraph Infiniti biofeedback apparatus, which is used specifically to train ADHD individuals to increase their attentive abilities. HRV was determined by time-domain, frequency-domain and Poincaré analysis of RR interval data. Skin conductivity was determined by BioGraph Infiniti biofeedback apparatus. Cardiac functioning of the children was assessed at baseline by means of blood pressure recordings and electrocardiograms (ECGs). Blood pressure was measured by means of a stethoscope and mercurial sphygmomanometer. ECGs were obtained by means of a Schiller CardioLaptop AT-110 ECG recorder using the standard 12-lead cable positioning for a resting ECG and parameters measured included HR, RR, QT, JT, QTc, JTc, QTd, JTd, QTcd and JTcd. EEG values were determined at baseline and during focussed attention by means of BioGraph Infiniti biofeedback apparatus. EEG values measured in this study included theta/beta ratios, theta/SMR ratios and thalpha, low alpha and high alpha power. The main findings of this study are that: <ul> <li>Stimulant-free ADHD children show a parasympathetic dominance of the sympathovagal balance relative to controls.</li> <li>Methylphenidate usage shifts the autonomic balance of children with ADHD towards normal levels; however a normal autonomic balance is not reached.</li> <li>Stimulant-free ADHD children exhibit a shift in the sympathovagal balance towards the sympathetic nervous system from baseline to focussed attention; however, methylphenidate abolishes this shift.</li> <li>Methylphenidate usage does not, in general, cause QTc or JTc prolongation but it may cause QTc or JTc prolongation in susceptible individuals.</li> <li>Children with ADHD can not be differentiated from normal children on the basis of theta/beta ratios, theta/SMR ratios or alpha power.</li> <li>Methylphenidate increases the level of centering in children with ADHD.</li> <li>Stimulant-free ADHD children display an alpha block from baseline to focussed attention; however, methylphenidate abolishes this alpha block.</li></ul> Copyright / Dissertation (MSc)--University of Pretoria, 2009. / Physiology / unrestricted

Cette thèse s'inscrit dans le contexte de l'analyse des signaux biomédicaux multicapteurs par des méthodes stochastiques. Les signaux auxquels nous nous intéressons présentent un caractère oscillant transitoire bien représenté par les décompositions dans le plan temps-fréquence c'est pourquoi nous avons choisi de considérer non plus les décours temporels de ces signaux mais les coefficients issus de la décomposition de ces derniers dans le plan temps-fréquence. Dans une première partie, nous décomposons les signaux multicapteurs sur une base de cosinus locaux (appelée base MDCT) et nous modélisons les coefficients à l'aide d'un modèle à états latents. Les coefficients sont considérés comme les réalisations de processus aléatoires gaussiens multivariés dont la distribution est gouvernée par une chaîne de Markov cachée. Nous présentons les algorithmes classiques liés à l'utilisation des modèles de Markov caché et nous proposons une extension dans le cas où les matrices de covariance sont factorisées sous forme d'un produit de Kronecker. Cette modélisation permet de diminuer la complexité des méthodes de calcul numérique utilisées tout en stabilisant les algorithmes associés. Nous appliquons ces modèles à des données électroencéphalographiques et nous montrons que les matrices de covariance représentant les corrélations entre les capteurs et les fréquences apportent des informations pertinentes sur les signaux analysés. Ceci est notamment illustré par un cas d'étude sur la caractérisation de la désynchronisation des ondes alpha dans le contexte de la sclérose en plaques. / This thesis adresses the problem of multichannel biomedical signals analysis using stochastic methods. EEG signals exhibit specific features that are both time and frequency localized, which motivates the use of time-frequency signal representations. In this document the (time-frequency labelled) coefficients are modelled as multivariate random variables. In the first part of this work, multichannel signals are expanded using a local cosine basis (called MDCT basis). The approach we propose models the distribution of time-frequency coefficients (here MDCT coefficients) in terms of latent variables by the use of a hidden Markov model. In the framework of application to EEG signals, the latent variables describe some hidden mental state of the subject. The latter control the covariance matrices of Gaussian vectors of fixed-time vectors of multi-channel, multi-frequency, MDCT coefficients. After presenting classical algorithms to estimate the parameters, we define a new model in which the (space-frequency) covariance matrices are expanded as tensor products (also named Kronecker products) of frequency and channels matrices. Inference for the proposed model is developped and yields estimates for the model parameters, together with maximum likelihood estimates for the sequences of latent variables. The model is applied to electroencephalogram data, and it is shown that variance-covariance matrices labelled by sensor and frequency indices can yield relevant informations on the analyzed signals. This is illustrated with a case study, namely the detection of alpha waves in rest EEG for multiple sclerosis patients and control subjects.