Selection of the Best Set of Features for sEMG-Based Hand Gesture Recognition Applying a CNN Architecture

The classification of surface myoelectric signals (sEMG) remains a great challenge when focused on its implementation in an electromechanical hand prosthesis, due to its nonlinear and stochastic nature, as well as the great difference between models applied offline and online. In this work, the sele...

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Detalles Bibliográficos
Autores principales: Sandoval-Espino, Jorge Arturo, Zamudio-Lara, Alvaro, Marbán-Salgado, José Antonio, Escobedo-Alatorre, J. Jesús, Palillero-Sandoval, Omar, Velásquez-Aguilar, J. Guadalupe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269838/
https://www.ncbi.nlm.nih.gov/pubmed/35808467
http://dx.doi.org/10.3390/s22134972

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269838/
https://www.ncbi.nlm.nih.gov/pubmed/35808467
http://dx.doi.org/10.3390/s22134972

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