Motion intention recognition of the affected hand based on the sEMG and improved DenseNet network
The key to sEMG (surface electromyography)-based control of robotic hands is the utilization of sEMG signals from the affected hand of amputees to infer their motion intentions. With the advancements in deep learning, researchers have successfully developed viable solutions for CNN (Convolutional Ne...
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| Principais autores: | , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Elsevier
2024-03-01
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| Colecção: | Heliyon |
| Assuntos: | |
| Acesso em linha: | http://www.sciencedirect.com/science/article/pii/S2405844024027944 |
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