Finger language recognition based on ensemble artificial neural network learning using armband EMG sensors

BACKGROUND: Deaf people use sign or finger languages for communication, but these methods of communication are very specialized. For this reason, the deaf can suffer from social inequalities and financial losses due to their communication restrictions. OBJECTIVE: In this study, we developed a finger...

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Detalles Bibliográficos
Autores principales: Kim, Seongjung, Kim, Jongman, Ahn, Soonjae, Kim, Youngho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IOS Press 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6005006/
https://www.ncbi.nlm.nih.gov/pubmed/29710753
http://dx.doi.org/10.3233/THC-174602

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6005006/
https://www.ncbi.nlm.nih.gov/pubmed/29710753
http://dx.doi.org/10.3233/THC-174602

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