Cargando…
Learning Data Correction for Myoelectric Hand Based on “Survival of the Fittest”
In recent years, myoelectric hands have become multi-degree-of-freedom (DOF) devices, which are controlled via machine learning methods. However, currently, learning data for myoelectric hands are gathered manually and thus tend to be of low quality. Moreover, in the case of infants, gathering accur...
Autores principales: | Yamanoi, Yusuke, Togo, Shunta, Jiang, Yinlai, Yokoi, Hiroshi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AAAS
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9494700/ https://www.ncbi.nlm.nih.gov/pubmed/36285147 http://dx.doi.org/10.34133/2021/9875814 |
Ejemplares similares
-
Coevolution of Myoelectric Hand Control under the Tactile Interaction among Fingers and Objects
por: Kuroda, Yuki, et al.
Publicado: (2022) -
Development of a Parent Wireless Assistive Interface for Myoelectric Prosthetic Hands for Children
por: Hiyoshi, Yutaro, et al.
Publicado: (2018) -
Design of an Effective Prosthetic Hand System for Adaptive Grasping with the Control of Myoelectric Pattern Recognition Approach
por: Wang, Yanchao, et al.
Publicado: (2022) -
Development of an sEMG sensor composed of two-layered conductive silicone with different carbon concentrations
por: Togo, Shunta, et al.
Publicado: (2019) -
Survey on Main Drive Methods Used in Humanoid Robotic Upper Limbs
por: Wang, Yiwei, et al.
Publicado: (2021)