sEMG-Based Robust Recognition of Grasping Postures with a Machine Learning Approach for Low-Cost Hand Control
The data presented in this study from the NinaPro Database are openly available at https://ninapro.hevs.ch/instructions/DB5.html (accessed on 21 March 2024). The data from UJIdb presented in this study are available upon request from the corresponding author.
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/389660 |
| Acceso en línea: | http://hdl.handle.net/10261/389660 https://api.elsevier.com/content/abstract/scopus_id/85190280701 |
| Access Level: | acceso abierto |
| Palabra clave: | EMG HRI Artificial hand Grasping postures Low-cost devices Machine learning Recognition |
| Sumario: | The data presented in this study from the NinaPro Database are openly available at https://ninapro.hevs.ch/instructions/DB5.html (accessed on 21 March 2024). The data from UJIdb presented in this study are available upon request from the corresponding author. |
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