EEG, EMG, and single cell activity were examined under states of animal hypnosis, sleep, and wakefulness. Rabbits and chickens were repetitively hypnotized to determine whether animal hypnosis was caused by a fear reaction. Differential susceptibility of chickens and rabbits to animal hypnosis suggests that more than a "paralysis of terror" is involved in causing this state. There was a difference in theta frequency in records from moving and still animals, and a 13-18 Hz component appeared on many records during synchronized and desynchronized sleep. A large number of cells fired with respect to certain EEG conditions rather than to a behavioural state. EEG and single cell activity obtained during early hypnosis were very similar to those appearing in an animal that was sitting alert. / Thesis / Doctor of Philosophy (PhD)

No / The use of electroencephalograms (EEGs) to diagnose and analyses Alzheimer's disease (AD) has received much attention in recent years. The sample entropy (SE) has been widely applied to the diagnosis of AD. In our study, nine EEGs from 21 scalp electrodes in 3 AD patients and 9 EEGs from 3 age-matched controls are recorded. The calculations show that the kurtoses of the AD patients' EEG are positive and much higher than that of the controls. This finding encourages us to introduce a kurtosis-based de-noising method. The 21-electrode EEG is first decomposed using independent component analysis (ICA), and second sort them using their kurtoses in ascending order. Finally, the subspace of EEG signal using back projection of only the last five components is reconstructed. SE will be calculated after the above de-noising preprocess. The classifications show that this method can significantly improve the accuracy of SE-based diagnosis. The kurtosis analysis of EEG may contribute to increasing the understanding of brain dysfunction in AD in a statistical way.

The electroencephalogram (EEG) reflects summated, slow post-synaptic potentials of cortical neurons. Sensory, motor or cognitive events (such as a fast-rising sensory stimulus, a brisk self-paced movement or a stimulus-triggered cognitive task) can elicit transient changes in the ongoing human EEG, called event-related potentials (ERPs). ERPs are widely used in clinical practice, and believed to reflect the activity of the sensory system activated by the stimulus (for example, laser-evoked potentials are used to substantiate the neuropathic nature of clinical pain conditions). When ERPs are elicited by pairs or trains of stimuli delivered at short inter-stimulus intervals (ISIs), the magnitude of the ERP elicited by the repeated stimuli is markedly reduced, a phenomenon known as response decrement. While the interval between two consecutive stimuli becomes longer, the reduced response is recovered. Thus, this phenomenon has been traditionally interpreted in terms of neural refractoriness of generators of ERPs ("neural refractoriness hypothesis"). This thesis, however, challenges this neural refractoriness hypothesis by describing the results of manipulating the preceding events of the eliciting stimulus. The first study examined the effect of variable and short ISIs on sensory ERPs, delivering trains of auditory and electrical stimuli with random ISIs ranging from 100 to 1000ms. In the second study, pairs of laser stimuli were presented in two comparable conditions. In the constant condition, the ISI was identical across trials in each block, while in the variable condition, the ISI was variable across trials. By directly comparing ERPs elicited by laser stimulation, this study aimed to explore whether lack of saliency in the eliciting stimulus could explain the response decrement during stimulus repetition. Finally, the third study tested the hypothesis that the reduced eliciting ERPs would recover if saliency were introduced by changing the modality of the preceding event. Thus, trains of three stimuli (S1-S2-S3) with 1s ISI were presented; S2 was either same or different in modality as S1 and S3 in each block. Results from these three experiments demonstrate that this "refractoriness hypothesis" does not hold, and suggest that the magnitude of ERPs is only partly related to the magnitude of the incoming sensory input, and instead largely reflects neural activities triggered by salient events in the sensory environment. These results are important for the correct interpretation of ERPs in both physiological and clinical studies.

This research has developed a novel method which uses an easy to deploy single dry electrode wireless electroencephalogram (EEG) collection device as an input to an automated system that measures indicators of a participant’s attentiveness while they are watching a short training video. The results are promising, including 85% or better accuracy in identifying whether a participant is watching a segment of video from a boring scene or lecture, versus a segment of video from an attentiveness inducing active lesson or memory quiz. In addition, the final system produces an ensemble average of attentiveness across many participants, pinpointing areas in the training videos that induce peak attentiveness. Qualitative analysis of the results of this research is also very promising. The system produces attentiveness graphs for individual participants and these triangulate well with the thoughts and feelings those participants had during different parts of the videos, as described in their own words. As distance learning and computer based training become more popular, it is of great interest to measure if students are attentive to recorded lessons and short training videos. This research was motivated by this interest, as well as recent advances in electronic and computer engineering’s use of biometric signal analysis for the detection of affective (emotional) response. Signal processing of EEG has proven useful in measuring alertness, emotional state, and even towards very specific applications such as whether or not participants will recall television commercials days after they have seen them. This research extended these advances by creating an automated system which measures attentiveness towards short training videos. The bulk of the research was focused on electrical and computer engineering, specifically the optimization of signal processing algorithms for this particular application. A review of existing methods of EEG signal processing and feature extraction methods shows that there is a common subdivision of the steps that are used in different EEG applications. These steps include hardware sensing filtering and digitizing, noise removal, chopping the continuous EEG data into windows for processing, normalization, transformation to extract frequency or scale information, treatment of phase or shift information, and additional post-transformation noise reduction techniques. A large degree of variation exists in most of these steps within the currently documented state of the art. This research connected these varied methods into a single holistic model that allows for comparison and selection of optimal algorithms for this application. The research described herein provided for such a structured and orderly comparison of individual signal analysis and feature extraction methods. This study created a concise algorithmic approach in examining all the aforementioned steps. In doing so, the study provided the framework for a systematic approach which followed a rigorous participant cross validation so that options could be tested, compared and optimized. Novel signal analysis methods were also developed, using new techniques to choose parameters, which greatly improved performance. The research also utilizes machine learning to automatically categorize extracted features into measures of attentiveness. The research improved existing machine learning with novel methods, including a method of using per-participant baselines with kNN machine learning. This provided an optimal solution to extend current EEG signal analysis methods that were used in other applications, and refined them for use in the measurement of attentiveness towards short training videos. These algorithms are proven to be best via selection of optimal signal analysis and optimal machine learning steps identified through both n-fold and participant cross validation. The creation of this new system which uses signal processing of EEG for the detection of attentiveness towards short training videos has created a significant advance in the field of attentiveness measuring towards short training videos.

Master of Science / Department of Clinical Sciences / Luciana Bergamasco / As public concern for food animal welfare increases, the need for objective pain assessment and methods to alleviate pain associated with production practices such as castration gains attention. The aims of this study were (i) to evaluate the physiological response to pain induced by castration in calves and (ii) to elucidate age-related differences in pain response of calves subjected to different castration methods. Seventy six Holstein bull calves were blocked by age (≤ 6 weeks and ≥ 6 months) and randomly assigned to one of four treatment groups: control (n = 20), castration by banding (n = 18), cut and clamp surgical castration (n = 20), and cut and pull surgical castration (n = 18). Measurements included electroencephalogram, heart rate variability, infrared thermography, electrodermal activity, and concentrations of serum cortisol, and plasma substance P prior to, during, and following castration. Electroencephalogram recordings showed desynchronization for all treatments, consistent with increased arousal; yet the magnitude of desynchronization was greatest for 6-month-old calves castrated by cut and clamp. Additionally, older calves in the cut and pull group showed greater desynchronization than younger calves in the same group. Based on the heart rate variability analysis, 6-month-old calves in the control or cut and pull castration groups showed greater sympathetic tone than younger calves in the same treatment groups. Overall, younger calves showed lower electrodermal activity than older calves. Regardless of treatment, concentrations of cortisol and plasma substance P were greater in 6-month-old calves relative to their younger counterparts. In summary, neurohormonal and electroencephalographic stress responses of calves to castration were age-specific. Castration by cut and clamp showed the most pronounced stress response in 6-month-old calves.

O ácido indol-3-acético (AIA) é um produto do metabolismo do triptofano encontrado nos organismos animais, vegetais e em microrganismos. Destacam-se os trabalhos que atribuíram ao AIA efeitos tanto antioxidantes quanto proxidantes em diferentes sistemas biológicos. O objetivo do presente estudo foi o de avaliar os efeitos da administração do AIA no metabolismo muscular e cerebral e na atividade elétrica cerebral de ratos. Foram realizados dois grupos de experimentos. No primeiro grupo foram avaliados os seguintes parâmetros: taxa glicêmica e o ganho de peso corporal de animais tratados por 14 dias com AIA (40 mg/Kg de peso vivo, via intragástrica); atividade das enzimas antioxidantes glutationa redutase (GR), catalase (CAT) e superóxido dismutase (SOD) e das enzimas do metabolismo da glicose hexoquinase (HQ), lactato desidrogenase (LDH) e glicose-6-fosfato desidrogenase (G6PDH) nos músculos sóleo e gastrocnêmio e a atividade da enzimas antioxidantes GR, CAT e SOD e a quantificação dos produtos resultantes da peroxidação lipídica (TBARs) no cérebro de ratos tratados por 14 dias com diferentes doses de AIA (1, 18 e 40 mg/Kg de peso animal, via intragástrica). Os respectivos controles de todas essas análises foram obtidos de ratos que receberam 1 mL de tampão fosfato pH 7,4 via intragástrica sob as mesmas condições experimentais. No segundo grupo de experimentos foi obtido o eletroencefalograma (EEG) dos animais. O EEG obtido foi filtrado nas bandas de freqüências delta (0,3-4 Hz), teta (4-8 Hz), alfa (8-12 Hz) e beta (12-30 Hz) e em cada banda calculou-se a energia do sinal. Foram avaliados o EEG de animais tratados com AIA (40 mg/Kg de peso vivo) e tratados com triptofano (40 mg/Kg de peso animal), ambos por via intragástrica. Os controles para esses tratamentos foram o EEG coletado 1 hora antes e 1 hora depois da administração de 1mL de tampão fosfato por via intragástrica no mesmo animal que recebeu o tratamento. Os resultados foram analisados por ANOVA com significância de 0,05 usando o teste de Tuckey e os estimadores foram validados usando-se bootstrap. A adminitração de AIA (40mg/Kg de peso vivo) não alterou a taxa glicêmica e evolução de peso corporal dos animais, em relação ao controle. Não foram observadas diferenças significativas entre os resultados obtidos de amostras de animais tratados com AIA (todas as doses) em relação aos respectivos controles para: atividade das enzimas antioxidantes muscular e cerebral; enzimas envolvidas com o metabolismo da glicose muscular; conteúdo de peroxidação lipídica (TBARs) cerebral. O método não invasivo de aquisição de EEG desenvolvido para ratos permitiu adquirir e analisar o sinal elétrico cerebral. Não foram observadas alterações no padrão do EEG após a administração de tampão fosfato. No entanto, o AIA na dose de 40 mg/Kg de peso vivo alterou o padrão do EEG do animal, pois, a energia das freqüências de ondas alfa (8-12 Hz) e beta (12-30 Hz) foi maior em relação ao estado normal e após administração de tampão fosfato. Já o triptofano na dose de 40 mg/Kg de peso vivo aumentou a energia da onda delta (0,3-4 Hz) e diminuiu na energia da onda beta (12-30 Hz) em relação ao estado normal. O método não invasivo de EEG para rato desenvolvido neste trabalho foi sensível para detectar a atividade elétrica encefálica dos animais e o triptofano serviu como parâmetro de referência, pois promoveu diferentes alterações no padrão do EEG daquelas observadas nos animais tratados com AIA. Conclui-se que o AIA não interferiu nos parâmetros metabólicos oxidativos e energéticos dos músculos e do cérebro dos animais estudados, mas promoveu alterações fisiológicas que desencadearam as mudanças observadas na energia do sinal de EEG dos animais. / Indole-3-acetic acid (IAA) is a tryptophan metabolic found in animals organisms, microorganisms and vegetables. It is remarkable the work done to IAA antioxidants and proxidants effects in several biological systems. The main purpose of these studies was to evaluate the effects of intragastric IAA administration in brain and in muscle metabolism and electrical brain activities in rat. The experiments were done in two groups. The first one, were evaluated the following parameters: glycemic rate and corporal gain weight to those animals treated14 days with IAA (40 mg/Kg of body weight); activity of antioxidants enzymes as glutathione reductase (GR), catalase (CAT), superoxide dismutase (SOD); activities of hexokinase (HQ), lactate dehidrogenase (LDH) and glucose-6-phosphate dehidrogenase (G6PDH) on soleus and gastrocnemic muscle; antioxidants enzymes activities and level of tiobarbituric reactives subtances (TBARs) in brain from rats treated during 14 days with doses of IAA (1,18 and 40 Kg/kg body of weight). All those analyses controls were obtained from rat that was given 1 mL of phosphate buffered saline, pH 7 (PBS), under the same experiments conditions as the group treated with IAA. On the second group of experiments was evaluated EEG pattern obtained from fixed electrodes on the animal skin surface were not sedated, and shown at delta frequency (0.3-4 Hz), theta (4-8 Hz), alpha (8-12 Hz) and beta (12-30 Hz) and the energy of those band frequency was calculated using a developed algorithm software MATLAB®. EEG was evaluated from animals treated with IAA (40 mg/Kg body weight) and treated with tryptophan (40 mg/Kg body weight), both intragastric. The management control for those treatments were EEG collected 1 hour before and 1 hour after the intragstric administration of 1mL PBS at the same animal that received the treatment. The results were analysed by ANOVA with great significance of 0.05 using the Tukey test and were evaluated by bootstrap. The IAA administration (40 mg/Kg body weight) did not change the glycaemia rate and the animal weight evolution, to compare with the control. Were not observed any significant differences among results from animals treated with IAA (all doses) relating to respective controls to: a) brain and muscles antioxidants enzymes activity; b) activities of enzymes with muscular glucose metabolism; c) brain lipid peroxidation contents by TBARs level. No invasive EEG colleting methods developed for rat allowed to collect and analyse electric brain signal. After an administration of PBS, were not observed any changes at EEG pattern. IAA dose of 40 mg/Kg body weight did change the animal EEG standard, the frequency energy of alpha wave to (8-12 Hz) and beta (12-30 Hz) was higher then normal after administration of PBS. On the other side, tryptophan dose of 40 mg/Kg body weight increased the delta wave energy to (0,3-4 Hz) and decreased the beta wave energy to (12-30 Hz), to compare withfthe normal standard. Non invasion EEG colleting methods for rat developed in this studies was sensible in order to detect an animals electric encephalic activity and the tryptophan became as reference parameter, due to several changes on pattern EEG to those animals treated with IAA. Concluding that, IAA did not interfere on oxidative metabolic parameters, neither to the brain and muscles of the studied animals, but promoted physiological changes that was possible to observe on animals electroencephalogram.

This thesis combines phenomenological and neuroscientific research to elucidate the effects of psychedelic agents on the human brain, mind and psychological well-being. Psychoactive plants have been used for thousands of years for ceremonial and ritual purposes. Psychedelics are psychoactive substances that affect cognitive processes and alter perception, thoughts, and mood. Illegalization of psychedelics in the 1960s rendered them impossible to study empirically but in the last couple of decades, relaxed legal restrictions regarding research purposes, renewed interest in the effects of psychedelic drugs and new brain imaging techniques have started to reveal the possibilities of these mind-altering substances. Psychedelics mainly affect the serotonin receptor 5-HT2A which in turn affect the functioning of largescale cortical areas by changing cerebral blood flow, alpha oscillations, and functional connectivity. These cortical changes not only induce immediate alterations in perception and cognition but have been shown to have positive effects in therapeutic interventions for depression, anxiety, and addiction, and also positively affect well-being in general. Although the pharmacology and neurobiology of psychedelics are still poorly understood, the potential benefits justify empirical research on psychedelics in humans.

Orientador: Ney Lemke / Resumo: O sono (do latim, somnus) é um período que apresenta uma atividade fisiológica característica, que pode ser registrada com o EEG. Algumas ondas em um sinal de EEG são vistas apenas durante o sono, como os fusos do sono e complexos K. O fuso é um dos elementos mais bem conhecidos no estudo do sono. No presente estudo serão estudados fusos globais e potenciais complexos K, os quais são observados simultaneamente em todos os canais de EEG. Para isto, um novo método de investigação foi proposto, que estuda tanto o envelope do sinal quanto a fase/frequência de cada fuso. Através da análise da fase do fuso global, foi mostrado que 90% dos fusos de indivíduos saudáveis sincronizam com um tempo de latência de 0,11s. O método também avalia a frequência de modulação (chirp) de fusos globais, e foi averiguado que não há correlação entre o chirp destes fusos e sua sincronização. Através do estudo do envelope do sinal juntamente com a implementação de um modelo de propagação isotrópico, foi possível estimar a origem do fuso e sua velocidade de propagação. Os resultados obtidos indicam que através desta abordagem simples e não invasiva é possível determinar, com uma precisão razoável, o local de origem dos fusos do sono, e sua velocidade estimada de propagação de 0,12m/s. Os potenciais complexos K detectados foram usados para avaliar a robustez do método desenvolvido, e apresentaram frequências, durações e amplitudes dentro das faixas esperadas para complexos K. A velocidade do propagação ... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Sleep (derived from the Latim, somnus) is a brain state with distinct physiological activity that can be investigated by EEG evaluation. Some waves are unique in sleep EEG such as sleep spindles and K complexes. Spindles are one of the best known elements in sleep studies. In this work we considered global spindles and K complexes, which are spindles that are observed simultaneously in all EEG channels. We propose a method that investigates both the signal envelope and phase/frequency of each global spindle. By analysing the spindle phase we showed that 90% of spindles in healthy subjects synchronize with a median latency time of 0.11 s. The method also measured the frequency slope (chirp) of global spindles and found that global spindle chirp and synchronization are not correlated. By investigating the signal envelopes and implementing a homogeneous and isotropic propagation model, we could estimate both the signal origin and velocity in global spindles. Our results indicate that this simple and non-invasive approach could determine with reasonable precision the spindle origin, and allowed us to estimate a signal speed of 0.12 m/s.Potential K complexes are used to assess the robustness of developed method and shows that frequencies, durations and amplitudes within the K complex expected range. Propagation velocity in potential K complexes are around 0.05 m/s which is lower than spindles velocity. Partial synchronization tendencies were detected in potential K complex, a... (Complete abstract click electronic access below) / Doutor

SUMMARY Introduction: There has recently been a great deal of interest in the role of synchronous high-frequency gamma oscillations in brain function. This interest has been motivated by an increasing body of evidence, that oscillations which are synchronous in phase across separated neuronal populations, may represent an important mechanism by which the brain binds or integrates spatially distributed processing activity which is related to the same object. Many models of schizophrenia suggest an impairment in the integration of brain processing, such as a loosening of associations, disconnection, defective multiple constraint organization, or cognitive dysmetria. This has led to recent speculation that abnormalities of high-frequency gamma synchronization may reflect a core dimension of the disturbance underlying this disorder. However, examination of the phase synchronization of gamma oscillations in patients with schizophrenia has never been previously undertaken. Method: In this thesis a new method of analysis of gamma synchrony was introduced, which enables the phase relationships of oscillations in a specific frequency band to be examined across multiple scalp sites as a function of time. This enabled, for the first time, the phase synchronization of gamma oscillations across widespread regions, to be studied in electrical brain activity measured at the scalp in humans. Gamma synchrony responses were studied in electroencephalographic (EEG) data acquired during a commonly employed conventional auditory oddball paradigm. The research consisted of two sets of experiments. In the first set of experiments, data from 100 normal subjects, consisting of 10 males and 10 females in each age decade from 20 to 70, was examined. These experiments were designed to characterize the gamma synchonizations that occurred in response to target and background stimuli and their functional significance in normal brain activity, and to exclude the possibility of these findings being due to electromyogram (EMG) or volume conduction artifact. The examination of functional significance involved the development of an additional new analysis technique. In the second set of experiments, data acquired from 35 patients with schizophrenia and 35 matched normal controls was analyzed. The purpose of these experiments was to determine whether patients showed disturbances of gamma synchrony compared to controls, and to establish the relationship of any such disturbances to medication levels, symptom profiles, duration of illness, and a range of psychophysiological variables. Results: In the 100 normals, responses to target stimuli were characterized by two bursts of synchronous gamma oscillations, an early (evoked) and a late (induced) synchronization, with different topographic distributions. Only the early gamma synchronization was seen in response to background stimuli. The main variable modulating the magnitude of these gamma synchronizations from epoch to epoch was pre-stimulus EEG theta (3-7 Hz) and delta (1-3 Hz) power. Early and late gamma synchrony were also associated with N1 and P3 ERP component amplitude across epochs. Across subjects, the early gamma synchronization was associated with shorter latency of the ERP components P2, N2 and P3, smaller amplitude of N1 and P2, and smaller pre-stimulus beta power. The control analyses showed that these gamma responses were specific to a narrow frequency range (37 to 41 Hz), and were not present in adjacent frequency bands. The responses were not generated by EMG contamination or volume conduction. In the 35 patients with schizophrenia, significant abnormalities of both the early and late synchronizations were observed compared to the 35 normal controls, with distinctive topographic characteristics. In general, early gamma synchrony was increased in patients compared to controls, and late gamma synchrony was decreased. These gamma synchrony disturbances were not related to medication level or the four summed symptom profile scores (positive, negative, general and total). They were, however, associated with duration of illness, becoming less severe the longer the patient had suffered from the disorder. The disordered gamma synchrony in patients was not secondary to abnormalities in other psychophysiological variables, but appeared to represent a primary disturbance. Discussion: The early synchronization may relate to the binding of object representations in early sensory processing, or, given that a constant inter-stimulus interval was employed, may be anticipatory and related to active memory. The late response is probably involved in binding in relation to activation of the internal contextual model involved in late expectancy/contextual processing (context updating or context closure) for target stimuli. The across epochs effects may relate to whether the focus of attention immediately prior to stimulus presentation is internal or is directed at the task. The across subjects effects suggest that a larger magnitude of the early gamma synchronization might indicate that the subject maintains a more stable and less ambiguous internal representation of the environment, that reduces the complexity of input and facilitates target/background discrimination and subsequent processing. The early gamma synchronization findings in patients with schizophrenia suggest that anticipatory processing involving active memory and forward-prediction of the environment is subject to over-binding or the formation of inappropriate associations. The late synchronization disturbances may reflect a fragmentation of contextual processing, and an inability to maintain contextual models of the environment intact over time. Conclusion: This research demonstrates the potential importance of integrative network activity as indexed by gamma phase synchrony in relation to normal cognition, and the possible broad relevance of such activity in psychiatric disorders. In particular, the application in this study to patients with schizophrenia showed that an impairment of brain integrative activity (missing links) might be a key feature of this illness.

Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) is a serious sleep disordered affecting up to 24% of men and 9% of woman in the middle aged population. The current standard for the OSAHS diagnosis is Polysomnography (PSG), which refers to the continuous monitoring of multiple physiological variables over the course of a night. The main outcomes of the PSG test are the OSAHS severity measures, such as the Respiratory Disturbance Index (RDI), Arousal Index, Latencies and other information to determine the macro sleep architecture (MSA), which is defined by Wake, Rapid-eye-movement (REM) and non-REM states of sleep. The MSA results are essential for computing the diagnostic measures reported in a PSG. The existing methods of the MSA analysis require the recording of 5-7 electrophysiological signals, including the Electroencephalogram (EEG), Electroculogram (EOG), and the Electromyogram (EMG). Sleep clinicians have to depend on the manual scoring of the overnight data records using the criteria given by Rechtschaffen and Kales (R&K, 1968). The manual analysis of MSA is tedious, subjective and suffers from inter- and intra-scorer variability. Additionally, the RDI and the Apnea-Hypopnea Index (AHI) parameters although used as the primary measures of the OSAHS severity, suffers from subjectivity, low reproducibility and a poor correlation with the symptoms of OSAHS. Sleep is essentially a neuropsychological phenomenon, and the EEG remains the best technique for the functional imaging of the brain during sleep. The EEG is the direct result of the neuronal activity of the brain. However, despite the potential, the wealth of information available in the EEG signal remains virtually untapped in current OSAHS diagnosis. Although the EEG is extensively used in traditional sleep analysis, its usage is mainly limited to staging sleep, based on the four-decade old R&K criteria. This thesis addresses these issues plaguing the PSG. We develop a novel, fully-automated algorithm (Higher-order Estimated Sleep States, HESS-algorithm) for the MSA analysis, which requires only one channel of the EEG data. We also develop an objective MSA analysis technique that uses a single, one-dimensional slice of the Bispectrum of the EEG, representing a nonlinear transformation of a system function that can be considered as the EEG generator. The agreement between the human and the proposed technology was found to be in the range of 70%-87%, which are similar to those, possible between expert human scorers. The ability of the HESS algorithm to compute the MSA parameters reliably and objectively will make a dramatic impact on the diagnosis and treatment of OSAHS and other sleep diseases, such as insomnia. The proposed technology uses low-computation-load Bispectrum techniques independent of R&K Criteria (1968) making real-time automated analysis a reality. In the thesis we also propose a new index (the IHSI) to characterise the severity of sleep apnea. The new index is based on the hemispherical asymmetry of the brain and is computed from the EEG coherence analysis. We achieved a significant (p=0.0001) accuracy of up to 91% in classifying patients into apneic and non-apneic group. Our statistical analysis results show that the IHSI carries potential for providing us with a reproducible measure to assist in diagnosing of OSAHS. With the proposed methods in this thesis it may be possible to develop the technology that will not only attempt to screen the OSAHS patients but will be able to provide OSAHS diagnosis with detailed sleep architecture via home based test. These technologies will simplify the instrumentation dramatically and will make possible to extend EEG/MSA analysis to portable systems as well.