Interpreting Deep Learning Features for Myoelectric Control: A Comparison With Handcrafted Features

Existing research on myoelectric control systems primarily focuses on extracting discriminative characteristics of the electromyographic (EMG) signal by designing handcrafted features. Recently, however, deep learning techniques have been applied to the challenging task of EMG-based gesture recognit...

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Detalles Bibliográficos
Autores principales: Côté-Allard, Ulysse, Campbell, Evan, Phinyomark, Angkoon, Laviolette, François, Gosselin, Benoit, Scheme, Erik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Bioengineering and Biotechnology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7063031/
https://www.ncbi.nlm.nih.gov/pubmed/32195238
http://dx.doi.org/10.3389/fbioe.2020.00158

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7063031/
https://www.ncbi.nlm.nih.gov/pubmed/32195238
http://dx.doi.org/10.3389/fbioe.2020.00158

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