A SE-DenseNet-LSTM model for locomotion mode recognition in lower limb exoskeleton

Locomotion mode recognition in humans is fundamental for flexible control in wearable-powered exoskeleton robots. This article proposes a hybrid model that combines a dense convolutional network (DenseNet) and long short-term memory (LSTM) with a channel attention mechanism (SENet) for locomotion mo...

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Principais autores:	Jing Tang, Lun Zhao, Minghu Wu, Zequan Jiang, Jiaxun Cao, Xiang Bao
Format:	Artigo
Jezik:	Inglês
Izdano:	PeerJ Inc. 2024-02-01
Serija:	PeerJ Computer Science
Teme:	Locomotion mode recognition Dense convolutional network Long short-term memory Lower limb exoskeleton
Online dostop:	https://peerj.com/articles/cs-1881.pdf
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