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Artifact removal from sEMG signals recorded during fully unsupervised daily activities
OBJECTIVE: In this study, we propose a method for removing artifacts from superficial electromyography (sEMG) data, which have been widely proposed for health monitoring because they encompass the basic neuromuscular processes underlying human motion. METHODS: Our method is based on a spectral sourc...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
SAGE Publications
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028668/ https://www.ncbi.nlm.nih.gov/pubmed/36960030 http://dx.doi.org/10.1177/20552076231164239 |