Algorithms for classification of a single channel EMG signal for human-computer interaction

Abstract

One of the most accurate and effective ways to control gestures is to control muscle activity, which occurs with any movement. Electromyography (EMG) is used to record such activity. This article compares SVM classification algorithms, perceptron, random trees and the method of density of probability in relation to the EMG signal. Arduino Leonardo with a single-channel Shield EMG is used to record the signal. The aim of this paper is to prove the possibility of creating a cheap and accessible biointerface based on EMG signal.