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Mobile robot control via brain computer interface and fatigue detection based on EEG signals / Younes Moussaoui

Public ISBD Titre : Mobile robot control via brain computer interface and fatigue detection based on EEG signals Type de document : document électronique Auteurs : Younes Moussaoui, Auteur ; Mahdi Latreche, Auteur ; Tadjine, Mohamed, Directeur de thèse ; Chakir, Messaoud, Directeur de thèse ; Guiatni, Mohamed, Directeur de thèse Editeur : [S.l.] : [s.n.] Année de publication : 2021 Importance : 132 f., 1 fichier PDF (10 Mo) Présentation : ill. Format : 30 cm Note générale : Mode d'accès : accès au texte intégral par intranet. Mémoire de Projet de Fin d’Études : Automatique : Alger, École Nationale Polytechnique : 2021 Bibliogr. f. 125-132 Langues : Anglais (eng) Mots-clés : EEG BCI Motor  imagery Fatigue Feature  extraction Machine  learning Deep Learning Genetic  algorithm Résumé : In the last decade, the rapid development of complex methods for recording brain signals and the exponential rise of available computing power as well as the increased awareness of brain dysfunctions and mental disorders, have led researchers to use large-scale neurophysiological recordings for abnormal behaviours detection, diseases diagnosis, and motor control. Electroencephalograms (EEG) are a very popular measurement for brain activities because of their non-invasive nature and their wide spectrum of possible applications. In this context, two applications have been developed in this project, the first aims to design a novel Brain Computer Interface (BCI) architecture based on Motor Imagery (MI) for real time control of a mobile robot. Spectral power computing, multi-class Common Spatial Pattern (CSP), and Machine Learning (ML) have been used to reach this aim. The second involves the proposal of an approach for fatigue detection using machine Learning (ML), Deep Learning (DL), and Genetic Algorithms (GA). Mobile robot control via brain computer interface and fatigue detection based on EEG signals [document électronique] / Younes Moussaoui, Auteur ; Mahdi Latreche, Auteur ; Tadjine, Mohamed, Directeur de thèse ; Chakir, Messaoud, Directeur de thèse ; Guiatni, Mohamed, Directeur de thèse . - [S.l.] : [s.n.], 2021 . - 132 f., 1 fichier PDF (10 Mo) : ill. ; 30 cm. Mode d'accès : accès au texte intégral par intranet. Mémoire de Projet de Fin d’Études : Automatique : Alger, École Nationale Polytechnique : 2021 Bibliogr. f. 125-132 Langues : Anglais (eng) Mots-clés : EEG BCI Motor  imagery Fatigue Feature  extraction Machine  learning Deep Learning Genetic  algorithm Résumé : In the last decade, the rapid development of complex methods for recording brain signals and the exponential rise of available computing power as well as the increased awareness of brain dysfunctions and mental disorders, have led researchers to use large-scale neurophysiological recordings for abnormal behaviours detection, diseases diagnosis, and motor control. Electroencephalograms (EEG) are a very popular measurement for brain activities because of their non-invasive nature and their wide spectrum of possible applications. In this context, two applications have been developed in this project, the first aims to design a novel Brain Computer Interface (BCI) architecture based on Motor Imagery (MI) for real time control of a mobile robot. Spectral power computing, multi-class Common Spatial Pattern (CSP), and Machine Learning (ML) have been used to reach this aim. The second involves the proposal of an approach for fatigue detection using machine Learning (ML), Deep Learning (DL), and Genetic Algorithms (GA).

Exemplaires

Code-barres	Cote	Support	Localisation	Section	Disponibilité	Spécialité	Etat_Exemplaire
03	PA00521	Ressources électroniques	Bibliothèque centrale	Projet Fin d'Etudes	Disponible	Automatique	Téléchargeable

Modeling identification and control of peltier thermoelectic modules for telepresence / Guiatni, Mohamed in Transactions of the ASME . Journal of dynamic systems, measurement, and control, Vol. 133 N° 3 (Mai 2011) 

Public ISBD [article]  in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 133 N° 3 (Mai 2011) . - 08 p. Titre : Modeling identification and control of peltier thermoelectic modules for telepresence Type de document : texte imprimé Auteurs : Guiatni, Mohamed, Auteur ; Kheddar, Abderrahmane, Auteur Année de publication : 2011 Article en page(s) : 08 p. Note générale : Systèmes dynamiques Langues : Anglais (eng) Mots-clés : Autoregressive  moving  average  processes  Heat  pumps  Peltier  effect  Telecontrol  Thermal  conductivity Index. décimale : 629.8 Résumé : This research deals with thermal rendering for telepresence applications. We present the modeling and identification of thermo-electric modules (TEMs) to be used either as part of a thermal display or a remote thermal probe. First, TEMs are modeled in steady- and unsteady-state dynamics using recursive nonlinear autoregressive moving average models for both temperature and heat flux. The proposed models are convenient for simulation, control, electronic, and thermal engineering. They allow understanding the functionality of the heat pumps and facilitate the solving of cooling/heating problems without the need for expertise in thermal theory. Then, these models are used in a novel thermal rendering approach that is based on the estimation of the temperature in contact for both the finger and the probed remote object in a telepresence setup. The thermal feedback is provided by a bilateral control between the master (thermal display) and the slave (thermal probe robotic finger). Experimental results validating the models and the proposed thermal rendering scheme are presented and discussed. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://asmedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA00013300 [...] [article] Modeling identification and control of peltier thermoelectic modules for telepresence [texte imprimé] / Guiatni, Mohamed, Auteur ; Kheddar, Abderrahmane, Auteur . - 2011 . - 08 p. Systèmes dynamiques Langues : Anglais (eng) in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 133 N° 3 (Mai 2011) . - 08 p. Mots-clés : Autoregressive  moving  average  processes  Heat  pumps  Peltier  effect  Telecontrol  Thermal  conductivity Index. décimale : 629.8 Résumé : This research deals with thermal rendering for telepresence applications. We present the modeling and identification of thermo-electric modules (TEMs) to be used either as part of a thermal display or a remote thermal probe. First, TEMs are modeled in steady- and unsteady-state dynamics using recursive nonlinear autoregressive moving average models for both temperature and heat flux. The proposed models are convenient for simulation, control, electronic, and thermal engineering. They allow understanding the functionality of the heat pumps and facilitate the solving of cooling/heating problems without the need for expertise in thermal theory. Then, these models are used in a novel thermal rendering approach that is based on the estimation of the temperature in contact for both the finger and the probed remote object in a telepresence setup. The thermal feedback is provided by a bilateral control between the master (thermal display) and the slave (thermal probe robotic finger). Experimental results validating the models and the proposed thermal rendering scheme are presented and discussed. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://asmedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA00013300 [...]