Creation of the Facial Gestures Dlassifier Based on the Electromyogram Analysis

The article presents the results of an experiment on the facial muscles electromyographic signal processing (EMG) based on the algorithm of radial basis function neural networks (NN). We have studied the efficiency of using as input for training NN nine signs of EMG learned as a function of time. The best result was obtained for the criterion Maximum Picked Value. The worst result was obtained for the criterion Mean Value. We have proposed a gesture recognition algorithm. The resulting algorithm and the neural network based on it can be used in the construction of a human-machine interface.