Análise da sonolência na condução rodoviária a partir de sinais EEG

A Sociedade Europeia de Pesquisa do Sono realizou muito recentemente um estudo, onde mostrou que a prevalência média de adormecimento ao volante nos últimos 2 anos foi de 17%. Além disto, tem sido provado por todo o mundo que a sonolência durante a condução é uma das principais causas de acidentes de trânsito. Torna-se assim conveniente, o desenvolvimento de sistemas que analisem a suscetibilidade de um determinado condutor para adormecer no trânsito, bem como de ferramentas que monitorem em tempo real o estado físico e mental do condutor, para alertarem nos momentos críticos. Apesar do estudo do sono se ter iniciado há vários anos, a maioria das investigações focaram-se no ciclo normal do sono, estudando os indivíduos de forma relaxada e de olhos fechados. Só mais recentemente, têm surgido os estudos que se focam nas situações de sonolência em atividade, como _e o caso da condução. Uma grande parte Dos estudos da sonolência em condução têm utilizado a eletroencefalografia (EEG), de forma a perceber se existem alterações nas diferentes bandas de frequência desta, que possam indicar o estado de sonolência do condutor. Além disso, a evolução da sonolência a partir de alterações no piscar dos olhos (que podem ser vistas nos sinais EEG) também tem sido alvo de grande pesquisa, tendo vindo a revelar resultados bastante promissores. Neste contexto e em parceria com a empresa HealthyRoad, esta tese está integrada no projeto HealthyDrive, que visa o desenvolvimento de um sistema de alerta e deteção de sinais de fadiga e sonolência nos condutores de veículos automóveis. A contribuição desta tese no projeto prendeu-se com o estudo da sonolência dos indivíduos em condução a partir de sinais EEG, para desta forma investigar possíveis indicadores dos diferentes níveis desta que possam ser utilizados pela empresa no projeto. Foram recolhidos e analisados 17 sinais EEG de indivíduos em simulação de condução. Além disso foram desenvolvidos dois métodos de análise destes sinais: O primeiro para a deteção e análise dos piscar de olhos a partir de EEG, o segundo para análise do espetro de potência. Ambos os métodos foram utilizados para analisar os sinais recolhidos e investigar que tipo de relação existe entre a sonolência do condutor e as alterações nos piscares dos olhos, bem como as alterações do espetro do EEG. Os resultados mostraram uma correlação entre a duração do piscar de olhos e a sonolência do condutor. Com o aumento da sonolência velicou-se um aumento da duração do piscar, desencadeado principalmente pelo aumento na duração de fecho, que chegou aos 51.2%. Em relação ao espectro de potência, os resultados sugerem que a potência relativa de todas as bandas analisadas fornecem informações relevantes sobre a sonolência do condutor. Além disso, o parâmetro (_+_)/_ demostrou estar relacionado com variações da sonolência, diminuindo com o seu avanço e aumentando significativamente (111%) no instante em que os condutores adormeceram.

Diagnostic yield of short-term video-EEG monitoring for epilepsy and PNESs: a European assessment.

INTRODUCTION: Although long-term video-EEG monitoring (LVEM) is routinely used to investigate paroxysmal events, short-term video-EEG monitoring (SVEM) lasting <24 h is increasingly recognized as a cost-effective tool. Since, however, relatively few studies addressed the yield of SVEM among different diagnostic groups, we undertook the present study to investigate this aspect. METHODS: We retrospectively analyzed 226 consecutive SVEM recordings over 6 years. All patients were referred because routine EEGs were inconclusive. Patients were classified into 3 suspected diagnostic groups: (1) group with epileptic seizures, (2) group with psychogenic nonepileptic seizures (PNESs), and (3) group with other or undetermined diagnoses. We assessed recording lengths, interictal epileptiform discharges, epileptic seizures, PNESs, and the definitive diagnoses obtained after SVEM. RESULTS: The mean age was 34 (±18.7) years, and the median recording length was 18.6 h. Among the 226 patients, 127 referred for suspected epilepsy - 73 had a diagnosis of epilepsy, none had a diagnosis of PNESs, and 54 had other or undetermined diagnoses post-SVEM. Of the 24 patients with pre-SVEM suspected PNESs, 1 had epilepsy, 12 had PNESs, and 11 had other or undetermined diagnoses. Of the 75 patients with other diagnoses pre-SVEM, 17 had epilepsy, 11 had PNESs, and 47 had other or undetermined diagnoses. After SVEM, 15 patients had definite diagnoses other than epilepsy or PNESs, while in 96 patients, diagnosis remained unclear. Overall, a definitive diagnosis could be reached in 129/226 (57%) patients. CONCLUSIONS: This study demonstrates that in nearly 3/5 patients without a definitive diagnosis after routine EEG, SVEM allowed us to reach a diagnosis. This procedure should be encouraged in this setting, given its time-effectiveness compared with LVEM.

Towards high-quality simultaneous EEG-fMRI at 7T: Detection and reduction of EEG artifacts due to head motion.

The enhanced functional sensitivity offered by ultra-high field imaging may significantly benefit simultaneous EEG-fMRI studies, but the concurrent increases in artifact contamination can strongly compromise EEG data quality. In the present study, we focus on EEG artifacts created by head motion in the static B0 field. A novel approach for motion artifact detection is proposed, based on a simple modification of a commercial EEG cap, in which four electrodes are non-permanently adapted to record only magnetic induction effects. Simultaneous EEG-fMRI data were acquired with this setup, at 7T, from healthy volunteers undergoing a reversing-checkerboard visual stimulation paradigm. Data analysis assisted by the motion sensors revealed that, after gradient artifact correction, EEG signal variance was largely dominated by pulse artifacts (81-93%), but contributions from spontaneous motion (4-13%) were still comparable to or even larger than those of actual neuronal activity (3-9%). Multiple approaches were tested to determine the most effective procedure for denoising EEG data incorporating motion sensor information. Optimal results were obtained by applying an initial pulse artifact correction step (AAS-based), followed by motion artifact correction (based on the motion sensors) and ICA denoising. On average, motion artifact correction (after AAS) yielded a 61% reduction in signal power and a 62% increase in VEP trial-by-trial consistency. Combined with ICA, these improvements rose to a 74% power reduction and an 86% increase in trial consistency. Overall, the improvements achieved were well appreciable at single-subject and single-trial levels, and set an encouraging quality mark for simultaneous EEG-fMRI at ultra-high field.

Charting developmental EEG gamma changes in the auditory modality /

The oscillation of neuronal circuits reflected in the EEG gamma frequency may be fundamental to the perceptual process referred to as binding (the integration of various thoughts and perceptions into a coherent picture). The aim of our study was to expand our knowledge of the developmental course ofEEG gamma in the auditory modality. 2 We investigated EEG 40 Hz gamma band responses (35.2 to 43.0 Hz) using an auditory novelty oddball paradigm alone and with a visual-number-series distracter task in 208 participants as a function of age (7 years to adult) at 9 sites across the sagital and lateral axes (F3, Fz, F4, C3, Cz, C4, P3, Pz, P4). Gamma responses were operationally defined as change in power or a change in phase synchrony level from baseline within two time windows. The evoked gamma response was defined as a significant change from baseline occurring between 0 to 150 ms after stimulus onset; the induced gamma response was measured from 250 to 750 ms after stimulus onset. A significant evoked gamma band response was found when measuring changes in both power and phase synchrony. The increase in both measures was maximal at frontal regions. Decreases in both measures were found when participants were distracted by a secondary task. For neither measure were developmental effects noted. However, evoked gamma power was significantly enhanced with the presentation of a novel stimulus, especially at the right frontal site (F4); frontal evoked gamma phase synchrony also showed enhancement for novel stimuli but only for our two oldest age groups (16-18 year olds and adults). Induced gamma band responses also varied with task-dependent cognitive stimulus properties. In the induced gamma power response in all age groups, target stimuli generated the highest power values at the parietal region, while the novel stimuli were always below baseline. Target stimuli increased induced synchrony in all regions for all participants, but the novel stimulus selectively affected participants dependent on their age and gender. Adult participants, for example, exhibited a reduction in gamma power, but an increase in synchrony to the novel stimulus within the same region. Induced gamma synchrony was more sensitive to the gender of the participant than was induced gamma power. While induced gamma power produced little effects of age, gamma synchrony did have age effects. These results confirm that the perceptual process which regulates gamma power is distinct from that which governs the synchronization for neuronal firing, and both gamma power and synchrony are important factors to be considered for the "binding" hypothesis. However, there is surprisingly little effect of age on the absolute levels of or distribution of EEG gamma in the age range investigated.

A microanalysis of EMG and EEG changes during the sleep onset period (SOP) : a theoretical investigation with practical applications /

The present study has both theoretical and practical aspects. The theoretical intent of the study was to closely examine the relationship between muscle activity (EMG) and EEG state during the process of falling asleep. Sleep stages during sleep onset (SO) have been generally defined with regards to brain wave activity (Recht schaff en & Kales (1968); and more precisely by Hori, Hayashi, & Morikawa (1994)). However, no previous study has attempted to quantify the changes in muscle activity during this same process. The practical aspect of the study examined the reliability ofa commercially developed wrist-worn alerting device (NovAlert™) that utilizes changes in muscle activity/tension in order to alert its user in the event that he/she experiences reduced wakefulness that may result in dangerous consequences. Twelve female participants (aged 18-42) sp-ent three consecutive nights in the sleep lab ("Adaptation", "EMG", and "NOVA" nights). Each night participants were given 5, twenty-minute nap opportunities. On the EMG night, participants were allowed to fall asleep freely. On the NOV A night, participants wore the Nov Alert™ wrist device that administered a Psychomotor Vigilance Test (PVT) when it detected that muscle activity levels had dropped below baseline. Nap sessions were scored using Hori's 9-stage scoring system (Hori et aI, 1994). Power spectral analyses (FFT) were also performed. Effects ofthe PVT administration on EMG and EEG frequencies were also examined. Both chin and wrist EMG activity showed reliable and significant decline during the early stages ofHori staging (stages HO to H3 characterized by decreases in alpha activity). All frequency bands studied went through significant changes as the participants progressed through each ofHori's 9 SO stages. Delta, theta, and sigma activity increased later in the SO continuum while a clear alpha dominance shift was noted as alpha activity shifted from the posterior regions of the brain (during Hori stages HO to H3) to the anterior portions (during Hori stages H7 to H9). Administration of the PVT produced significant increases in EMG activity and was effective in reversing subjective drowsiness experienced during the later stages of sleep onset. Limitations of the alerting effects of the PVTs were evident following 60 to 75 minutes of use in that PVTs delivered afterwards were no longer able to significantly increase EMG levels. The present study provides a clearer picture of the changes in EMG and EEG during the sleep onset period while testing the efficacy of a commercially developed alerting device. EMG decreases were found to begin during Hori stage 0 when EEG was - dominated by alpha wave activity and were maximal as Hori stages 2 to 5 were traversed (coincident with alpha and beta activity). This signifies that EMG decrements and the loss of resting alpha activity are closely related. Since decreased alpha has long been associated with drowsiness and impending sleep, this investigation links drops in muscle tone with sleepiness more directly than in previous investigations. The EMG changes were reliably demonstrated across participants and the NovAlert™ detected the EMG decrements when Hori stage 3 was entered. The alerting vibrations produced by the NovAlert™ occurred early enough in the SO process to be of practical importance as a sleepiness monitoring and alerting device.

Age-Related Changes in Visual Spatial Working Memory Cognits: Frontal-Parietal EEG Coherence During Delay

This study explored changes in scalp electrophysiology across two Working Memory (WM) tasks and two age groups. Continuous electroencephalography (EEG) was recorded from 18 healthy adults (18-34 years) and 12 healthy adolescents (14-17) during the performance of two Oculomotor Delayed Response (ODR) WM tasks; (i.e. eye movements were the metric of motor response). Delay-period, EEG data in the alpha frequency was sampled from anterior and parietal scalp sites to achieve a general measure of frontal and parietal activity, respectively. Frontal-parietal, alpha coherence was calculated for each participant for each ODR-WM task. Coherence significantly decreased in adults moving across the two ODR tasks, whereas, coherence significantly increased in adolescents moving across the two ODR tasks. The effects of task in the adolescent and adult groups were large and medium, respectively. Within the limits of this study, the results provide empirical support that WM development during adolescence include complex, qualitative, change.

Control of a tibio-femoral virtual joint by means of a hybrid EEG-EMG scheme.

Tesis (Master of Science in Electrical Engineering) UANL, 2014.

Étude de l'EEG quantifié en éveil et en sommeil chez des adolescents présentant un trouble anxieux

Les troubles anxieux sont parmi les troubles psychiatriques les plus souvent diagnostiqués chez les adolescents. Ces troubles sont souvent accompagnés de nombreuses comorbidités, dont des difficultés de sommeil. L’objectif principal de cette thèse est de caractériser l’activité corticale à l’éveil et pendant le sommeil à l’aide de l’EEG quantifié chez une population d’adolescents présentant un trouble anxieux, et de la comparer à un groupe témoin d’adolescents. Dans un second temps, on cherche à savoir si l’activité EEG des patients anxieux corrèle avec différentes mesures cliniques. Deux études permettent de répondre à ces objectifs, une première portant sur l’activité EEG au cours de l’éveil, et une seconde portant sur l’activité EEG au cours du sommeil (SL et SP). La première étude démontre que l’activité EEG des deux groupes ne présente pas de différence à l’EEG le soir. Par contre, le matin, les patients anxieux présentent une activité significativement supérieure à celle des contrôles aux électrodes centrales (0,75-10 Hz et 13-20 Hz) ainsi qu’aux électrodes occipitales (2,5-7,75 Hz). Dans la seconde étude, nous avons analysé l’activité EEG absolue et relative en SL et en SP. Nous avons trouvé une activité absolue significativement supérieure à l’EEG de la région centrale chez les participants du groupe anxieux : en SLP (stades 3 et 4) sur l’ensemble des bandes de fréquence, en stade 2 sur les bandes de fréquence thêta, alpha et beta seulement. Finalement, en SP, les différences sont trouvées en alpha et beta, et non en thêta et delta. Les résultats obtenus à ces deux études suggèrent la présence de mécanismes de synchronisation et de filtrage inadéquats au niveau de la boucle thalamo-corticale, entraînant une hypervigilance du SNC. Quant aux corrélations entre l’activité EEG et les mesures cliniques, les résultats obtenus dans les deux études révèlent que les fréquences lentes (thêta et delta) de l’activité d’éveil le matin corrèlent à la fois avec l’anxiété de trait et d’état et les fréquences rapides (Alpha et Beta) de l’EEG du sommeil corrèlent sélectivement avec l’anxiété d’état. Il semble donc exister un lien entre les mesures cliniques et l’activité EEG. Une hausse d’activité EEG pourrait être un indicateur de la sévérité accrue des symptômes anxieux.

Étude de L'EEG quantifié au cours du sommeil paradoxal dans le trouble du spectre autistique

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

Topographie de l’activité EEG en fuseaux au cours du sommeil chez des enfants et adultes autistes

Les fuseaux de sommeil sont des ondes électroencéphalographiques reflétant les mécanismes électrophysiologiques de protection du sommeil. Les adultes autistes ont un sommeil léger et moins de fuseaux de sommeil que des adultes neurotypiques. L’étude vérifie si les enfants autistes montrent également moins de fuseaux de sommeil que les enfants neurotypiques et documente leur évolution avec l’âge. Nous avons enregistré le sommeil de 34 adultes (16 autistes) et 26 enfants (13 autistes) et comparé la quantité de fuseaux de sommeil enregistrés aux électrodes préfrontales (Fp1, Fp2) et centrales (C3, C4). Les deux groupes montrent une diminution similaire des fuseaux en vieillissant. Le groupe d’enfants autistes montre moins de fuseaux que le groupe témoin aux électrodes Fp2 et C4; les adultes autistes montrent significativement moins de fuseaux que les adultes contrôles aux deux électrodes centrales. Le mauvais sommeil des autistes pourrait être causé par une faible protection du sommeil déjà présente en bas âge.