Publication:
Comparison of EMG based finger motion classification algorithms [EMG Tabanli parmak hareket siniflandirilma algoritmalarinin karşilaştirilmasi]

dc.contributor.authorsAltan E., Pehlivan K., Kaplanoglu E.
dc.date.accessioned2022-03-15T02:14:28Z
dc.date.accessioned2026-01-10T17:19:22Z
dc.date.available2022-03-15T02:14:28Z
dc.date.issued2019
dc.description.abstractThe electrical signs of the muscle cells in the human body are called myoelectric. EMG is the whole of the methods for obtaining and recording myoelectric signals in the human body. In this study, as pre-study of a myoelectric controlled prosthesis control, EMG signals that perceived from surface electrodes that were taken, processed and classified was performed. During the basic finger movement of the volunteers, the surface electrodes on the forearms and EMG signs of the flexor and extensor muscles were taken, amplified, digitized and transferred to the computer for analysis for classification. In MATLAB environment, finger movements are tried to be determined correctly by using Decision Tree, Support Vector Machine, K-Nearest Neighbors algorithms. © 2019 IEEE.
dc.identifier.doi10.1109/SIU.2019.8806331
dc.identifier.isbn9781728119045
dc.identifier.urihttps://hdl.handle.net/11424/248043
dc.language.isotur
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof27th Signal Processing and Communications Applications Conference, SIU 2019
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectDecision Tree
dc.subjectEMG
dc.subjectKNN
dc.subjectSVM
dc.subjectVariance
dc.titleComparison of EMG based finger motion classification algorithms [EMG Tabanli parmak hareket siniflandirilma algoritmalarinin karşilaştirilmasi]
dc.typeconferenceObject
dspace.entity.typePublication
oaire.citation.title27th Signal Processing and Communications Applications Conference, SIU 2019

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