Myoelectric Pattern Recognition Using Gramian Angular Field and Convolutional Neural Networks for Muscle–Computer Interface

In the field of the muscle–computer interface, the most challenging task is extracting patterns from complex surface electromyography (sEMG) signals to improve the performance of myoelectric pattern recognition. To address this problem, a two-stage architecture, consisting of Gramian angular field (...

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Detalles Bibliográficos
Autores principales: Fan, Junjun, Wen, Jiajun, Lai, Zhihui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007307/
https://www.ncbi.nlm.nih.gov/pubmed/36904918
http://dx.doi.org/10.3390/s23052715

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007307/
https://www.ncbi.nlm.nih.gov/pubmed/36904918
http://dx.doi.org/10.3390/s23052715

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