DocumentCode
274145
Title
Artificial neural net algorithms in classifying electromyographic signals
Author
Schizas, C.N. ; Pattichis, C.S. ; Schofield, I.S. ; Fawcett, P.R. ; Middleton, L.T.
Author_Institution
MDRTC, Neurodiagnostic Unit, Cyprus
fYear
1989
fDate
16-18 Oct 1989
Firstpage
134
Lastpage
138
Abstract
Examines how artificial neural nets (ANN) can be used as a computerized method for electromyographic diagnosis. For this reason, a number of well defined neuromuscular disorders have been selected: the Becker´s muscular dystrophy; the spinal muscular atrophy; and the motor neuron disease. In this study the macro motor unit potential shape descriptors form continuous valued inputs, which are used to excite a multilayer perceptron net. Learning is carried out under supervision by providing to the net the desired output
Keywords
bioelectric potentials; computerised pattern recognition; medical diagnostic computing; muscle; neural nets; patient diagnosis; Becker´s muscular dystrophy; artificial neural nets; computerised pattern recognition; electromyographic diagnosis; medical diagnostic computing; motor neuron disease; motor unit potential; multilayer perceptron net; neuromuscular disorders; spinal muscular atrophy;
fLanguage
English
Publisher
iet
Conference_Titel
Artificial Neural Networks, 1989., First IEE International Conference on (Conf. Publ. No. 313)
Conference_Location
London
Type
conf
Filename
51946
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