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Artykuły w czasopismach na temat "Signaux EEG cliniques"
Bertrand, Janie, Rita Sammour, Catherine Mccuaig, JoséE Dubois, Afshin Hatami, Sandra Ondrejchak, Christine Boutin, Patricia Bortoluzzi, Louise C. Laberge i Julie Powell. "Propranolol in the Treatment of Problematic Infantile Hemangioma: Review of 35 Consecutive Patients from a Vascular Anomalies Clinic". Journal of Cutaneous Medicine and Surgery 16, nr 5 (wrzesień 2012): 317–23. http://dx.doi.org/10.1177/120347541201600508.
Pełny tekst źródłaHui-Chih Wu, Julie, Bradley J. Langford, Kevin L. Schwartz, Rosemary Zvonar, Sumit Raybardhan, Valerie Leung i Gary Garber. "Potential Negative Effects of Antimicrobial Allergy Labelling on Patient Care: A Systematic Review". Canadian Journal of Hospital Pharmacy 71, nr 1 (9.03.2018). http://dx.doi.org/10.4212/cjhp.v71i1.1726.
Pełny tekst źródłaRozprawy doktorskie na temat "Signaux EEG cliniques"
Abazid, Majd. "Topological study of the brain functional organization at the early stages of Alzheimer's disease using electroencephalography". Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAS026.
Pełny tekst źródłaElectroencephalography (EEG) is still considered nowadays as a convenient neuroimaging technique in clinical applications, suitable for cognitively and physically disabled patients, as well as for serial tests. In fact, EEG is a non-invasive, cost-effective, and mobile technology. It is characterized by a high temporal resolution, which is crucial for the analysis of fast brain functional dynamics.There is a rich literature addressing the use of EEG to investigate brain activity alterations due to neurodegenerative diseases, especially Alzheimer's disease (AD). AD is a chronic neurodegenerative disease that leads to progressive decline of cognitive functions along with behavioral disorders and insidious loss of autonomy in daily living activities. We observe a growing interest in the earlier stages of the disease since curative treatments are still lacking. The preclinical stage of AD is asymptomatic, but the brain lesions due to AD are present. At this phase, the term of subjective cognitive impairment (SCI) has been recently defined. In the prodromal stage, mild cognitive impairment (MCI) patients show measurable memory impairments but their functional capacity is maintained. SCI and MCI patients are at high risk of developing AD.This thesis investigates the early diagnosis of AD at preclinical and prodromal stages using resting-state EEG, and addresses brain network analysis by studying the functional connectivity over several clinical stages of cognitive decline (SCI, MCI and Mild AD). To this end, we conduct a retrospective study using a clinical database that contains EEG signals recorded in real-life conditions.We first propose to exploit an entropy measure, termed “epoch-based entropy” (EpEn), as a measure of functional connectivity, that relies on a refined statistical modeling of EEG signals based on Hidden Markov Models. This measure characterizes the spatiotemporal changes in EEG signals by quantifying the information content of EEG signals, both at the time and spatial levels.Furthermore, we conduct a topological brain network analysis over the three stages of cognitive decline by employing the Graph Theory. The novelty of our work is twofold. Actually, this is the first work that: (i) addresses EEG brain network analysis over SCI, MCI and Mild AD stages simultaneously, and (ii) combines EpEn to Graph Theory since we have shown its effectiveness in quantifying the complete spatiotemporal alteration due to AD.In this thesis, we decided to invest the largest amount of EEG information for brain network analysis, by exploiting several frequency ranges (delta, theta, alpha, beta), several electrodes locations (instead of regions), and several network density scales (multiple graph thresholding). Therefore, another issue tackled in this thesis concerns the identification of relevant EEG markers to discriminate automatically between SCI, MCI and AD patients in the context of graph analysis framework. To this end, we propose an automatic hierarchical method for EEG analysis, which allows the extraction of relevant markers from large amount of information based on a single EEG connectivity measure.Finally, we also assess the correlation between the relevant EEG markers and the clinical markers at our disposal (MMSE, RL/RI-16, BREF)
Grouiller, Frédéric. "Cartographie fonctionnelle du cerveau épileptique lors des évaluations préchirurgicales". Phd thesis, Grenoble 1, 2008. http://www.theses.fr/2008GRE10116.
Pełny tekst źródłaMapping of epileptic networks is crucial during functional investigations in drug-resistant patients (30%). Recent advances in neuroimaging opened the possibility to record simultaneously fMRI and EEG. It appears as a technique perfectly suited to epilepsy evaluation because it allows identifying both functional and epileptic. The main goal of this PhD work was to develop EEG/fMRI procedures at the Grenoble Hospital for pre- and post-surgical brain mapping in epileptics. Potential clinical benefits are the improvement of surgical outcome by identifying epileptic networks, and the reduction of side-effects of surgery by preserving brain functions. Because EEG signals acquired in a magnetic environment are noisy, we first evaluated how the performance of different artefact removal algorithms depends on various experimental settings. Second, we assessed hemodynamic variability in EEG/fMRI recordings and proposed a robust method estimating the most suitable patient-specific hemodynamic response to improve the sensitivity of such exams. Our results show that (i) most of removal artefact methods are efficient but that over-filtering could deteriorate EEG; (ii) estimation of hemodynamic properties is critical for EEG/fMRI exams in epilepsy. This suggests that epilepsy is often accompanied by an alteration of brain hemodynamics. We have successfully implemented EEG/fMRI at the Grenoble Hospital. This technique appeared to be helpful for presurgical evaluations. However, because of heterogeneous neurovascular coupling, the interpretation of activation maps remains difficult. Therefore, characterizing epilepsy cannot be done solely using EEG/fMRI and needs complementary investigations
Grouiller, Frédéric. "Cartographie fonctionnelle du cerveau épileptique lors des évaluations préchirurgicales". Phd thesis, Université Joseph Fourier (Grenoble), 2008. http://tel.archives-ouvertes.fr/tel-00326577.
Pełny tekst źródłaL'objectif de cette thèse était la mise en place, au CHU de Grenoble, de protocoles d'acquisition et de traitement de l'IRMf/EEG afin de localiser les réseaux épileptiques lors des évaluations pré- et post-chirurgicales. Les bénéfices sont de maximiser les chances de guérison en identifiant le réseau épileptique et de limiter les effets secondaires en préservant les aires fonctionnelles.
L'acquisition de l'EEG en milieu magnétique produit des artefacts. Nous avons d'abord évalué la performance de plusieurs algorithmes de correction d'artefacts selon différentes configurations expérimentales. Nous avons ensuite évalué l'influence du couplage hémodynamique et proposé une méthode robuste estimant la réponse hémodynamique optimale pour chaque patient afin d'améliorer la sensibilité des examens.
Nos résultats montrent que (i) la plupart des algorithmes sont efficaces mais qu'un filtrage trop strict peut détériorer l'EEG ; (ii) l'estimation de la réponse hémodynamique est cruciale en IRMf/EEG. Ceci suggère que l'épilepsie peut induire une modification des propriétés hémodynamiques.
L'IRMf/EEG est une méthode prometteuse pour les investigations préchirurgicales. En raison de l'hétérogénéité du couplage neurovasculaire, l'interprétation des cartes d'activation reste délicate et nécessite l'emploi d'approches complémentaires.