Title :
Basing on RBF Neural Network to Classify Surface Electromyography
Author :
Shicai, Liu ; Qingju, Zhang ; Bo, Sun
Author_Institution :
Sch. of Inf., Linyi Univ., Linyi, China
Abstract :
In this paper, a method is presented, which bases on Power Spectrum and RBF neural network. First, we calculate Power Spectrum eigenvector that is pretreated. Second, using the Power Spectrum coefficient to train the RBF neural network and classify the muscle movement of forearm. The experiment indicates this measure can reduce workload and get the relatively good results.
Keywords :
eigenvalues and eigenfunctions; electromyography; learning (artificial intelligence); medical signal processing; radial basis function networks; RBF neural network training; forearm; muscle movement classification; power spectrum coefficient; power spectrum eigenvector; surface electromyography classification; Electrodes; Electromyography; Muscles; Pattern recognition; Radial basis function networks; Training; Wrist; Power Spectrum; RBF neural network; Signal; Surface Electromyography; pattern recognition;
Conference_Titel :
Instrumentation, Measurement, Computer, Communication and Control, 2011 First International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-0-7695-4519-6
DOI :
10.1109/IMCCC.2011.72
