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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...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Qunfeng Niu, Lei Shi, Yang Niu, Kunming Jia, Guangxiao Fan, Ranran Gui, Li Wang
Format: Artigo
Sprache:Inglês
Veröffentlicht: Elsevier 2024-03-01
Schriftenreihe:Heliyon
Schlagworte:
sEMG
Motion intention of the affected hand
Improved DenseNet
Channel optimization
PCMIRR
Online-Zugang:http://www.sciencedirect.com/science/article/pii/S2405844024027944
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