Year 2017, Volume 5 , Issue 2, Pages 97 - 101 2017-09-01

Emg Signal Classification Using Fuzzy Logic

Osman ULKIR [1] , Gokhan GOKMEN [2] , Erkan KAPLANOGLU [3]


Electromyography (EMG) signals are an important technique in the control applications of prostatic hand. These signals, which are measured from the skin surface, are used to perform movements such as wrist flexion / extension, forearm supination / pronation and hand opening / closing of prosthetic devices. In this study, root mean square, waveform length and kurtosis methods were applied to extracted EMG signals from flexor carpi radialis and extensor carpi radialis muscles by using two channel surface electrodes. A fuzzy logic based classification method has been applied to classify the extracted signal features. With this method, classification for different gripping movements has been successfully accomplished.   

Surface EMG, fuzzy logic, feature extraction, EMG classification
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Journal Section Araştırma Articlessi
Authors

Author: Osman ULKIR
Country: Turkey


Author: Gokhan GOKMEN
Country: Turkey


Author: Erkan KAPLANOGLU
Country: Turkey


Dates

Publication Date : September 1, 2017

Bibtex @research article { bajece337941, journal = {Balkan Journal of Electrical and Computer Engineering}, issn = {2147-284X}, address = {}, publisher = {Balkan Yayın}, year = {2017}, volume = {5}, pages = {97 - 101}, doi = {10.17694/bajece.337941}, title = {Emg Signal Classification Using Fuzzy Logic}, key = {cite}, author = {Ulkır, Osman and Gokmen, Gokhan and Kaplanoglu, Erkan} }
APA Ulkır, O , Gokmen, G , Kaplanoglu, E . (2017). Emg Signal Classification Using Fuzzy Logic . Balkan Journal of Electrical and Computer Engineering , 5 (2) , 97-101 . DOI: 10.17694/bajece.337941
MLA Ulkır, O , Gokmen, G , Kaplanoglu, E . "Emg Signal Classification Using Fuzzy Logic" . Balkan Journal of Electrical and Computer Engineering 5 (2017 ): 97-101 <https://dergipark.org.tr/en/pub/bajece/issue/36585/337941>
Chicago Ulkır, O , Gokmen, G , Kaplanoglu, E . "Emg Signal Classification Using Fuzzy Logic". Balkan Journal of Electrical and Computer Engineering 5 (2017 ): 97-101
RIS TY - JOUR T1 - Emg Signal Classification Using Fuzzy Logic AU - Osman Ulkır , Gokhan Gokmen , Erkan Kaplanoglu Y1 - 2017 PY - 2017 N1 - doi: 10.17694/bajece.337941 DO - 10.17694/bajece.337941 T2 - Balkan Journal of Electrical and Computer Engineering JF - Journal JO - JOR SP - 97 EP - 101 VL - 5 IS - 2 SN - 2147-284X- M3 - doi: 10.17694/bajece.337941 UR - https://doi.org/10.17694/bajece.337941 Y2 - 2017 ER -
EndNote %0 Balkan Journal of Electrical and Computer Engineering Emg Signal Classification Using Fuzzy Logic %A Osman Ulkır , Gokhan Gokmen , Erkan Kaplanoglu %T Emg Signal Classification Using Fuzzy Logic %D 2017 %J Balkan Journal of Electrical and Computer Engineering %P 2147-284X- %V 5 %N 2 %R doi: 10.17694/bajece.337941 %U 10.17694/bajece.337941
ISNAD Ulkır, Osman , Gokmen, Gokhan , Kaplanoglu, Erkan . "Emg Signal Classification Using Fuzzy Logic". Balkan Journal of Electrical and Computer Engineering 5 / 2 (September 2017): 97-101 . https://doi.org/10.17694/bajece.337941
AMA Ulkır O , Gokmen G , Kaplanoglu E . Emg Signal Classification Using Fuzzy Logic. Balkan Journal of Electrical and Computer Engineering. 2017; 5(2): 97-101.
Vancouver Ulkır O , Gokmen G , Kaplanoglu E . Emg Signal Classification Using Fuzzy Logic. Balkan Journal of Electrical and Computer Engineering. 2017; 5(2): 97-101.
IEEE O. Ulkır , G. Gokmen and E. Kaplanoglu , "Emg Signal Classification Using Fuzzy Logic", Balkan Journal of Electrical and Computer Engineering, vol. 5, no. 2, pp. 97-101, Sep. 2017, doi:10.17694/bajece.337941