Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/4265
Title: The Evaluation of Telecommunication Signal Processing Techniques for EMG Disease Classification
Other Titles: EMG’de Hastalık Sınıflandırması İçin Haberleşme Sinyal İşleme Tekniklerinin Değerlendirilmesi
Authors: Çevikgibi, Buğra Alp
Güngen, Murat Alp
Girici, Tolga
Keywords: EMG
myopathy
neuropathy
classification
EMG
Myopati
Nöropati
Sınıflandırma
Issue Date: Aug-2020
Publisher: IEEE
Source: Çevikgibi, B. A., Güngen, M. A., & Girici, T. EMG’de Hastalık Sınıflandırması İçin Haberleşme Sinyal İşleme Tekniklerinin Değerlendirilmesi.
Abstract: Electromyography (EMG) is a biological signal widely used in medical imaging. It is used by doctors for the classification and diagnosis of myopathic and neuropathic diseases. Many different techniques have been used to ease the diagnosis of these diseases like machine learning and support vector machines (SVM). In this work, various methods used in telecommunication systems for digital modulation identification have been used to extract features from EMG signals as potential features. The results show success in classifying between different types of EMG waveforms.
URI: https://hdl.handle.net/20.500.11851/4265
https://doi.org/10.1109/SIU49456.2020.9302330
ISSN: 2165-0608
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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