Overview of processing techniques for surface electromyography signals
Abstract
Surface electromyography (sEMG) is a technology to assess muscle activation, which is an important component in applications related to diagnosis, treatment, progression assessment, and rehabilitation of specific individuals' conditions. Recently, sEMG potential has been shown, since it can be used in a non-invasive manner; nevertheless, it requires careful signal analysis to support health professionals reliably. This paper briefly described the basic concepts involved in the sEMG, such as the physiology of the muscles, the data acquisition, the signal processing techniques, and classification methods that may be used to identify disorders or signs of abnormalities according to muscular patterns. Specifically, classification methods encompass digital signal processing techniques and machine learning with high potential in the field. We hope that this work serves as an introduction to researchers interested in this field.
Cite
@article{arxiv.2304.04098,
title = {Overview of processing techniques for surface electromyography signals},
author = {Alejandra Manjarres-Triana and Juan Acevedo-Serna and Andrés A. Ramírez-Duque and Mario F. Jiménez and Edith Pulido-Herrera and John J. Villarejo Mayor},
journal= {arXiv preprint arXiv:2304.04098},
year = {2023}
}
Comments
11 pages, 7 figures