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

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 probabilit...

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Bibliographic Details
Published in:ITM web of conferences 2018, Vol.18, p.2001
Main Authors: Lukyanchikov, Andrei, Melnikov, Alexei, Lukyanchikov, Oleg
Format: Article
Language:English
Subjects:
Algorithms
Biomedical materials
Classification
Electromyography
Interfaces
Muscles
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Summary: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.
ISSN:2271-2097
2431-7578
2271-2097
DOI:10.1051/itmconf/20181802001