TY  - JOUR
TT  - CLASSIFICATION OF EMG SIGNALS USING ARTIFICIAL NEURAL NETWORK AND  DIAGNOSIS OF NEUROPATHY NEUROMUSCULAR DISEASE
AU  - Hardalaç, Fırat
AU  - Poyraz, Mustafa
PY  - 2002
DA  - March
JF  - Politeknik Dergisi
PB  - Gazi University
WT  - DergiPark
SN  - 2147-9429
SP  - 75
EP  - 83
VL  - 5
IS  - 1
KW  - Yapay sinir ağı
KW  - Geri yayılım
KW  - Eşlenik gradyan ve Hızlıprop öğrenme algoritması
KW  - EMG
KW  - HFD
N2  - In this study, the fast Fourier transform (FFT) analysis was applied to EMG signals recorded from Abductor Pollicis Brevis (APB) First Dorsal Interosseous(FDI) ve Abductor Digiti Minimi(ADM) muscles of 59 patients. FFT coefficient obtained from the result of this application trained with backpropagation algorithm of artificial neural network (ANN) and classification for diagnosis was realized. Conjugate gradient and quickprop learning algorithms were used during this training. After 500 learning cycles (Epoch), performance values of test results was computed and compared. Consequently, FFT coefficients were trained in neural network and neuropathy and normal EMG signals were classified with correction rate of 97%
UR  - https://dergipark.org.tr/en/pub/politeknik/issue//366875
L1  - https://dergipark.org.tr/en/download/article-file/384303
ER  -