Gesture Classification in Electromyography Signals for Real-Time Prosthetic Hand Control Using a Convolutional Neural Network-Enhanced Channel Attention Model

Accurate and real-time gesture recognition is required for the autonomous operation of prosthetic hand devices. This study employs a convolutional neural network-enhanced channel attention (CNN-ECA) model to provide a unique approach for surface electromyography (sEMG) gesture recognition. The intro...

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Detalles Bibliográficos
Autores principales: Yu, Guangjie, Deng, Ziting, Bao, Zhenchen, Zhang, Yue, He, Bingwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10669079/
https://www.ncbi.nlm.nih.gov/pubmed/38002448
http://dx.doi.org/10.3390/bioengineering10111324

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10669079/
https://www.ncbi.nlm.nih.gov/pubmed/38002448
http://dx.doi.org/10.3390/bioengineering10111324

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