A Novel TCN-LSTM Hybrid Model for sEMG-Based Continuous Estimation of Wrist Joint Angles

Surface electromyography (sEMG) offers a novel method in human–machine interactions (HMIs) since it is a distinct physiological electrical signal that conceals human movement intention and muscle information. Unfortunately, the nonlinear and non-smooth features of sEMG signals often make joint angle...

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Auteurs principaux:	Jiale Du, Zunyi Liu, Wenyuan Dong, Weifeng Zhang, Zhonghua Miao
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2024-08-01
Collection:	Sensors
Sujets:	surface electromyography (sEMG) wrist kinematics estimation human–machine interaction (HMI) temporal convolution network (TCN) long short-term memory neural network (LSTM)
Accès en ligne:	https://www.mdpi.com/1424-8220/24/17/5631
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