Mapping from EMG Signals to Joint Angles in Walking Cats using Neural Networks (MLP/BP) and Support Vector Machines (SVM)
نویسنده
چکیده
This report presents the use of feed forward ANNs with accelerated Back propagation and Support Vector Regression to predict the joint angles of walking cats using the EMG signals obtained from several muscles of the cat hind and fore limbs. The MATLAB software was used with NN and SVM tools. The results have demonstrated that, both methods can be effectively used to predict the joint angles, if appropriate model architecture and input data are available. But the best prediction was obtained using SVR to predict the phase of the hip angle, that gives the other joint angles of each limb.
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