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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...

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Detalles Bibliográficos
Autores principales:	Costa-García, Álvaro, Okajima, Shotaro, Yang, Ningjia, Shimoda, Shingo
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	SAGE Publications 2023
Materias:	Original Research
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

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