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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...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| 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 |