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dc.contributor.authorArtuğ, Necdet Tuğrulen_US
dc.contributor.authorBolat, Bülenten_US
dc.contributor.authorOsman, Onuren_US
dc.contributor.authorGöker, İmranen_US
dc.contributor.authorTulum, Gökalpen_US
dc.contributor.authorBaslo, Mehmet Barışen_US
dc.date.accessioned2016-05-25T08:24:29Z
dc.date.available2016-05-25T08:24:29Z
dc.date.issued2014
dc.identifier.citationArtuğ, N. T., Bolat, B., Osman, O., Göker, İ., Tulum, G., Baslo, M. B. (2014). Feature Extraction and Classification of Neuromuscular Diseases Using Scanning EMG. IEEE International Symposium on Innovations in Intelligent Systems and Applications, Proceedings, 262-265.en_US
dc.identifier.isbn9781479930197
dc.identifier.urihttps://hdl.handle.net/20.500.12294/446
dc.identifier.urihttp://dx.doi.org/10.1109/INISTA.2014.6873628
dc.descriptionArtuğ, Necdet Tuğrul (Arel Author) Osman, Onur (Arel Author) Göker, İmran(Arel Author) --- Conference: IEEE International Symposium on Innovations in Intelligent Systems and Applications, 2014.en_US
dc.description.abstractIn this study a new dataset are prepared for neuromuscular diseases using scanning EMG method and four new features are extracted. These features are maximum amplitude, phase duration at the maximum amplitude, maximum amplitude times phase duration, and number of peaks. By using statistical values such as mean and variance, number of features has increased up to eight. This dataset was classified by using multi layer perceptron (MLP), support vector machines (SVM), k-nearest neighbours algorithm (k-NN), and radial basis function networks (RBF). The best accuracy is obtained as 97.78% with SVM algorithm and 3-NN algorithm.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFeature Extractionen_US
dc.subjectClassificationen_US
dc.subjectScanning EMGen_US
dc.subjectNeuromuscular Diseasesen_US
dc.titleFeature Extraction and Classification of Neuromuscular Diseases Using Scanning EMGen_US
dc.typeconferenceObjecten_US
dc.departmentİstanbul Arel Üniversitesi, Mühendislik ve Mimarlık Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü.en_US
dc.authoridTR46079en_US
dc.authoridTR174101en_US
dc.authoridTR13219en_US
dc.authoridTR40789en_US
dc.authoridTR160901en_US
dc.authoridTR13946en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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