A feature-based processing framework for real-time implementation of muscle fatigue measurement

P. González-Zamora, Victor H. Benitez, Jesus Pacheco*

*Autor correspondiente de este trabajo

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

1 Cita (Scopus)

Resumen

Electromyographic signals (EMGs) are becoming important as a tool for muscle fatigue monitoring. EMGs measure the electric currents produced in muscle contractions providing information that can be analyzed and processed to evaluate the conditions of muscles. In this work, we proposed a real-time system that measures muscle fatigue levels based on Electromyographic signals. We used the Mean Frequency and the Power Spectral Density as features for muscle fatigue determination. A linear regression model determines the levels of muscle fatigue. Moreover, the system is composed of EMG wireless sensors allowing it to be used in common activities in the manufacturing industry as manual handling loads.

Idioma originalInglés
Páginas (desde-hasta)385-394
Número de páginas10
PublicaciónCluster Computing
Volumen26
N.º1
DOI
EstadoPublicada - feb. 2023

Nota bibliográfica

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

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