摘要
The objective of the work is to investigate the classifcation of different movements based on the surface electromyogram(SEMG)pattern recognition method.The testing was conducted for four arm movements using several experiments with artificial neural network class fication scheme.Six time domain features were extracted and consequently dlassification was implemented using back propagation neural dassifier(BPNC).Further,the realization of projected network was verified using cross validation(CV)process;hence ANOVA algorithm was carried out.Performance of the network is analyzed by considering mean square error(MSE)value.A comparison was performed between the extracted feat ures and back propagation network results reported in the literature.The concurrent result indicates the significance of proposed network with classification accuracy(CA)of 100%recorded from two channels,while analysis of variance technique helps in investigating the effectiveness of classified sigmal for recognition tasks.
