Using LBG algorithm for extracting the features of EMG signals; [EMG i̇şaretlerinin özniteliklerinin belirlenmesinde LBG algoritmasinin kullanimi]

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dc.contributor.authorKoçyiǧit Y.
dc.contributor.authorKiliç I.
dc.date.accessioned2024-07-22T08:22:04Z
dc.date.available2024-07-22T08:22:04Z
dc.date.issued2008
dc.description.abstractThe Electromyographic (EMG) signals observed at the surface of the skin is the sum of many small action potentials generated in the muscle fibers. There is only a pattern for each EMG signals, which are generated by biceps and triceps muscles. There are different types of signal processing in order to find out the feature values for true classification in this pattern. In this study, the Feature values belong to 4 different arm movements are obtained by using clustering methods, i.e K-means, Fuzzy C-means, and LBG after applying Wavelet Transform to EMG signals . Then these feature values are compared each other by KEYK and Quadratic Discriminant Analysis classifier. ©2008 IEEE.
dc.identifier.DOI-ID10.1109/SIU.2008.4632551
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/18904
dc.language.isoTurkish
dc.subjectDiscriminant analysis
dc.subjectMuscle
dc.subjectSignal processing
dc.subjectWavelet transforms
dc.subjectAction potentials
dc.subjectArm movements
dc.subjectClustering methods
dc.subjectElectromyographic signals
dc.subjectEmg signals
dc.subjectFuzzy c-means
dc.subjectK-Means
dc.subjectLBG algorithms
dc.subjectMuscle fibers
dc.subjectQuadratic discriminant analyses
dc.subjectFeature extraction
dc.titleUsing LBG algorithm for extracting the features of EMG signals; [EMG i̇şaretlerinin özniteliklerinin belirlenmesinde LBG algoritmasinin kullanimi]
dc.typeConference paper

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