Neuronal spectral analysis of EEG and expert knowledge integration for automatic classification of sleep stages

Autor: Kerkeni, N., Alexandre, F., Mohamed Hédi BEDOUI, Bougrain, L., Dogui, M.
Přispěvatelé: Neuromimetic intelligence (CORTEX), INRIA Lorraine, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Technologie et Imagerie Médicale [Monastir] (TIM), Faculté de Médecine de Monastir [Tunisie], Service d'Exploration Fonctionnelle du Système Nerveux, Hôpital Universitaire Sahloul (CHU Sahloul)
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Zdroj: Scopus-Elsevier
WSEAS Transactions on Information Science and Applications
WSEAS Transactions on Information Science and Applications, World Scientific and Engineering Academy and Society (WSEAS), 2005, 2 (11), pp.1854-1861
WSEAS Transactions on Information Science and Applications, 2005, 2 (11), pp.1854-1861. ⟨10.48550/arXiv.cs/0510083⟩
ISSN: 1790-0832
2224-3402
DOI: 10.48550/arXiv.cs/0510083⟩
Popis: http://www.wseas.org; Being able to analyze and interpret signal coming from electroencephalogram (EEG) recording can be of high interest for many applications including medical diagnosis and Brain-Computer Interfaces. Indeed, human experts are today able to extract from this signal many hints related to physiological as well as cognitive states of the recorded subject and it would be very interesting to perform such task automatically but today no completely automatic system exists. In previous studies, we have compared human expertise and automatic processing tools, including artificial neural networks (ANN), to better understand the competences of each and determine which are the difficult aspects to integrate in a fully automatic system. In this paper, we bring more elements to that study in reporting the main results of a practical experiment which was carried out in an hospital for sleep pathology study. An EEG recording was studied and labeled by a human expert and an ANN. We describe here the characteristics of the experiment, both human and neuronal procedure of analysis, compare their performances and point out the main limitations which arise from this study.
Databáze: OpenAIRE
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