Ανάλυση σήματος ηλεκτροεγκεφαλογραφήματος κατά τη διάρκεια χειρονομίας αρπαγής για χρήση σε τηλεχειρισμό

Δημακόπουλος, Δημοσθένης; Dimakopoulos, Dimosthenis

dc.contributor.author	Δημακόπουλος, Δημοσθένης	el
dc.contributor.author	Dimakopoulos, Dimosthenis	en
dc.date.accessioned	2018-09-18T09:42:05Z
dc.date.available	2018-09-18T09:42:05Z
dc.date.issued	2018-09-18
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/47616
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.13875
dc.rights	Default License
dc.subject	Ηλεκτροεγκεφαλογράφημα	el
dc.subject	Τηλεχειρισμός ρομπότ	el
dc.subject	Επεξεργασία σήματος	el
dc.subject	Αρπαγή	el
dc.subject	Διεπαφές ανθρώπου-μηχανής	el
dc.subject	Electroencephalogram	en
dc.subject	Brain-machine interfaces	en
dc.subject	Teleoperation	en
dc.subject	Grasping	en
dc.subject	Signal processing	en
dc.title	Ανάλυση σήματος ηλεκτροεγκεφαλογραφήματος κατά τη διάρκεια χειρονομίας αρπαγής για χρήση σε τηλεχειρισμό	el
heal.type	bachelorThesis
heal.secondaryTitle	Analysis of electroencephalographic signals during grasping gesture for use in teleoperation	en
heal.classification	Επεξεργασία σήματος	el
heal.classification	Ρομποτική	el
heal.classificationURI	http://data.seab.gr/concepts/d4a2bbb7e49dc1c3b397d27e9041df8118db670b
heal.classificationURI	http://data.seab.gr/concepts/989f7eb5ce955dbf96b4eebf1ff0aaec33f7e858
heal.language	el
heal.access	free
heal.recordProvider	ntua	el
heal.publicationDate	2018-07
heal.abstract	Μελέτη και επεξεργασία Ηλεκτροεγκεφαλογραφικών σημάτων μέσω πειραματικής διεξαγωγής, με σκοπό την ταξινόμηση δύο καταστάσεων του χρήστη, της Χαλάρωσης και της Χειρονομίας Αρπαγής. Η ταξινόμηση των καταστάσεων αυτών έχει ως σκοπό την κατασκευή κατάλληλης Διεπαφής Εγκεφάλου-Υπολογιστή, για τον τηλεχειρισμό ρομπότ με προσθετικό χέρι για την αρπαγή αντικειμένων.	el
heal.abstract	The evolution of technology and the society we are part of and live has led to remarkable scientific steps to understand the human brain. Through the processing of electroencephalographic ( EEG ) signals we are now able to decode movements and patterns of a human body in order to build Brain-machine Interfaces capable of improving our way of life. EEG signals may be weak and contain a lot of noise but hide all the information we need to decode movements such as the gesture during the grasping of objects and succeed in the teleoperation of a robot with the noninvasive connection of the user with electrodes along the scalp. By researching the alpha and beta rhythms of the brain during resting and grasping phases and the Event-Related Desynchronization or Synchronization we can reach a satisfying classification of a user’s intent or condition. In this diploma thesis, we researched and processed the EEG signals recorded during an experimental set up where we succeeded in the classification of two phases of a user: the Resting Phase and the Grasping phases/conditions Interface for the teleoperation of robots with prosthetic hands for grasping objects. The experiments were designed with the thought of future applications in Virtual Reality environments where the user will be connected in such a virtual environment and control a robotic system with EEG signals only in order to grasp objects. phases/conditions Interface for the teleoperation of robots with prosthetic hands for grasping objects. The experiments were designed with the thought of future applications in Virtual Reality environments where the user will be connected in such a virtual environment and control a robotic system with EEG signals only in order to grasp objects. Phase. The satisfying classification of these two phases/conditions enables us to build a suitable Brain-machine Interface for the teleoperation of robots with prosthetic hands for grasping objects. The experiments were designed with the thought of future applications in Virtual Reality environments where the user will be connected in such a virtual environment and control a robotic system with EEG signals only in order to grasp objects.	en
heal.advisorName	Κυριακόπουλος, Κωνσταντίνος	el
heal.committeeMemberName	Παπαδόπουλος, Ευάγγελος	el
heal.committeeMemberName	Αντωνιάδης, Ιωάννης	el
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Μηχανολόγων Μηχανικών. Τομέας Μηχανολογικών Κατασκευών και Αυτομάτου Ελέγχου	el
heal.academicPublisherID	ntua
heal.numberOfPages	77 σ.	el
heal.fullTextAvailability	true