Publication:
The Research of Characteristic Frequencies for Gesture-based EMG Control Channels

Дата
2022
Авторы
Igrevskaya, A.
Kachina, A.
Petrova, A.
Kudryavtsev, K.
Journal Title
Journal ISSN
Volume Title
Издатель
Научные группы
Организационные подразделения
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Организационная единица
Институт интеллектуальных кибернетических систем
Цель ИИКС и стратегия развития - это подготовка кадров, способных противостоять современным угрозам и вызовам, обладающих знаниями и компетенциями в области кибернетики, информационной и финансовой безопасности для решения задач разработки базового программного обеспечения, повышения защищенности критически важных информационных систем и противодействия отмыванию денег, полученных преступным путем, и финансированию терроризма.
Выпуск журнала
Аннотация
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.The paper describes experimental studies of the selection of characteristic frequencies for use in EMG-based human-machine interfaces in the problem of gesture recognition. Such interfaces allow the operator to interact with a mobile robotic device without significant physical effort. The flexion of the hand fingers is characterized by neuromuscular temporal signals, which are read by sensors and subsequently subjected to mathematical processing. The discrete Fourier transform allows us to obtain a spectral representation of the signal and select the main frequencies where the maximum signal amplitude appears. The resulting frequency sets can be used to identify gestures and generate control commands for a robotic device. The selection of a frequency set was carried out for the particular case of recognizing the thumb flexion as a gesture. As a result, it was found that considered parameters are not resistant to the influence of various factors that also include the execution of other gestures. Therefore, it is also suggested to take into account the signal power at these frequencies.
Описание
Ключевые слова
Цитирование
The Research of Characteristic Frequencies for Gesture-based EMG Control Channels / Igrevskaya, A. [et al.] // Studies in Computational Intelligence. - 2022. - 1032 SCI. - P. 158-163. - 10.1007/978-3-030-96993-6_14
URI
https://www.doi.org/10.1007/978-3-030-96993-6_14
 https://www.scopus.com/record/display.uri?eid=2-s2.0-85127636712&origin=resultslist
 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS_CPL&DestLinkType=FullRecord&UT=WOS:000833484200014
 https://openrepository.mephi.ru/handle/123456789/28963
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