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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2019
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| 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 |