Balkan Journal of Electrical and Computer Engineering 2147-284X 2147-284X MUSA YILMAZ 10.17694/bajece.337941 Emg Signal Classification Using Fuzzy Logic Ulkır Osman Gokmen Gokhan Kaplanoglu Erkan 09 01 2017 5 2 97 101 09 12 2017 08 10 2017 Copyright © 2013, Balkan Journal of Electrical and Computer Engineering 2013 Balkan Journal of Electrical and Computer Engineering

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

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