A Bi-GRU-attention neural network to identify motor units from high-density surface electromyographic signals in real time

To utilize surface electromyographics (sEMG) for control purposes, it is necessary to perform real-time estimation of the neural drive to the muscles, which involves real-time decomposition of the EMG signals. In this paper, we propose a Bidirectional Gate Recurrent Unit (Bi-GRU) network with attent...

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Autors principals:	Chuang Lin, Chen Chen, Ziwei Cui, Xiujuan Zhu
Format:	Artigo
Idioma:	Inglês
Publicat:	Frontiers Media S.A. 2024-03-01
Col·lecció:	Frontiers in Neuroscience
Matèries:	real-time decomposition motor units blind source separation gate recurrent unit network attention
Accés en línia:	https://www.frontiersin.org/articles/10.3389/fnins.2024.1306054/full
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