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Inferring Static Hand Poses from a Low-Cost Non-Intrusive sEMG Sensor

Every year, a significant number of people lose a body part in an accident, through sickness or in high-risk manual jobs. Several studies and research works have tried to reduce the constraints and risks in their lives through the use of technology. This work proposes a learning-based approach that...

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Detalles Bibliográficos
Autores principales: Nasri, Nadia, Orts-Escolano, Sergio, Gomez-Donoso, Francisco, Cazorla, Miguel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359473/
https://www.ncbi.nlm.nih.gov/pubmed/30658480
http://dx.doi.org/10.3390/s19020371