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Gesture Classification Based on Electromyography



dc.contributor.advisorPošík Petr
dc.contributor.authorCaro Néstor
dc.date.accessioned2016-06-05T09:43:38Z
dc.date.available2016-06-05T09:43:38Z
dc.date.issued2016-05-27
dc.identifierKOS-593779561605
dc.identifier.urihttp://hdl.handle.net/10467/64858
dc.description.abstractThe purpose of the work is to identify different hand poses based in the Electromyography raw signals provided from a Myo armband, using various signal processing, feature extraction and pattern recognition techniques. First we will replicate the gesture dictionary provided by the manufacturer, and then we will explore different hand poses that are compatible with the basic dictionary of gestures, and then expanding the amount of recognizable gestures for the tested classifiers.cze
dc.description.abstractThe purpose of the work is to identify different hand poses based in the Electromyography raw signals provided from a Myo armband, using various signal processing, feature extraction and pattern recognition techniques. First we will replicate the gesture dictionary provided by the manufacturer, and then we will explore different hand poses that are compatible with the basic dictionary of gestures, and then expanding the amount of recognizable gestures for the tested classifiers.eng
dc.language.isoENG
dc.publisherČeské vysoké učení technické v Praze. Vypočetní a informační centrum.cze
dc.publisherCzech Technical University in Prague. Computing and Information Centre.eng
dc.rightsA university thesis is a work protected by the Copyright Act. Extracts, copies and transcripts of the thesis are allowed for personal use only and at one?s own expense. The use of thesis should be in compliance with the Copyright Act http://www.mkcr.cz/assets/autorske-pravo/01-3982006.pdf and the citation ethics http://www.cvut.cz/sites/default/files/content/d1dc93cd-5894-4521-b799-c7e715d3c59e/cs/20160901-metodicky-pokyn-c-12009-o-dodrzovani-etickych-principu-pri-priprave-vysokoskolskych.pdfeng
dc.rightsVysokoškolská závěrečná práce je dílo chráněné autorským zákonem. Je možné pořizovat z něj na své náklady a pro svoji osobní potřebu výpisy, opisy a rozmnoženiny. Jeho využití musí být v souladu s autorským zákonem http://www.mkcr.cz/assets/autorske-pravo/01-3982006.pdf a citační etikou http://www.cvut.cz/sites/default/files/content/d1dc93cd-5894-4521-b799-c7e715d3c59e/cs/20160901-metodicky-pokyn-c-12009-o-dodrzovani-etickych-principu-pri-priprave-vysokoskolskych.pdfcze
dc.subjectElectromyography, Machine Learning, Myo armbandcze
dc.subjectElectromyography, Machine Learning, Myo armbandeng
dc.titleKlasifikace gest založená na elektromyografiicze
dc.titleGesture Classification Based on Electromyographyeng
dc.typediplomová prácecze
dc.typemaster thesiseng
dc.date.accepted
dc.contributor.refereeChudáček Václav
theses.degree.disciplineRobotikacze
theses.degree.grantorkatedra kybernetikycze
theses.degree.programmeKybernetika a robotikacze


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