РАЗРАБОТКА И ИССЛЕДОВАНИЕ МЕТОДА ВЕКТОРНОГО АНАЛИЗА ЭМГ ПРЕДПЛЕЧЬЯ ДЛЯ ПОСТРОЕНИЯ ЧЕЛОВЕКО-МАШИННЫХ ИНТЕРФЕЙСОВ

Abstract

The paper deals with the problems of increasing the depth and increasing the long-term stabilityof communication channels in human-machine interfaces, built on the basis of data on theelectrical activity of the forearm muscles. A possible solution is to use the method of analysis ofelectromyogram (EMG) signals, which combines vector and command control. In view of the possibilityof random displacement of the position of the electrodes during operation, a mathematicalmodel was built for vector analysis of EMG in spherical coordinates, which is invariant to thespatial arrangement of the electrodes on the forearm. Command control is based on gesturerecognition by means of a pretrained artificial neural network (ANN). Vector control consists insolving the problem of calibrating the channels of EMG sensors according to the spatial arrangementof the electrodes and calculating the resulting vector of muscle forces used as an additionalinformation channel to set the direction of movement of the operating point of the control object.The proposed method has been tested on actually recorded EMG signals. The influence of theduration of the processed signal fragments on the process of extracting information about therotational movement of the hand was investigated. Since the change in the position of the electrodesbetween operating sessions is different, an algorithm for reassigning and calibrating theamplification of the EMG channels is presented, which makes it possible to use a once trainedANN for recognition and classification of gestures in the future. Practical application of the resultsof the work is possible in the development of algorithms for calibration, gesture recognitionand control of technical objects based on electromyographic human-machine interfaces.