Comparative Analysis of Efficiency of the Machine Learning Methods for Gesture Recognition Using Double-Channel Electromyography

Abstract The paper is devoted to the efficiency analysis of the machine learning methods for gesture recognition, which are applied to the surface double-channel electromyography data. The comparative analysis was conducted for recognition of eight types of palm movements. The results of the analysi...

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Bibliographic Details
Published inJournal of physics. Conference series Vol. 2134; no. 1; pp. 12010 - 12014
Main Authors Ponomarchuk, Y V, Kuznetsov, I V
Format Journal Article
LanguageEnglish
Published IOP Publishing 01.12.2021
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Summary:Abstract The paper is devoted to the efficiency analysis of the machine learning methods for gesture recognition, which are applied to the surface double-channel electromyography data. The comparative analysis was conducted for recognition of eight types of palm movements. The results of the analysis lead to conclusion that it is necessary to consider the muscle groups’ location for better recognition accuracy and the increase of the number of considered gestures.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2134/1/012010