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.

Detalles Bibliográficos
Autores: Mora, Marta C., García-Ortiz, José V, Cerdá-Boluda, Joaquín
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
Descripción
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.