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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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Detalhes bibliográficos
Publicado no:Sensors (Basel)
Main Authors: Nasri, Nadia, Orts-Escolano, Sergio, Gomez-Donoso, Francisco, Cazorla, Miguel
Formato: Artigo
Idioma:Inglês
Publicado em: MDPI 2019
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6359473/
https://ncbi.nlm.nih.gov/pubmed/30658480
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s19020371
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