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Silent Speech Decoding Using Spectrogram Features Based on Neuromuscular Activities
Silent speech decoding is a novel application of the Brain–Computer Interface (BCI) based on articulatory neuromuscular activities, reducing difficulties in data acquirement and processing. In this paper, spatial features and decoders that can be used to recognize the neuromuscular signals are inves...
Autores principales: | Wang, You, Zhang, Ming, Wu, RuMeng, Gao, Han, Yang, Meng, Luo, Zhiyuan, Li, Guang |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7407985/ https://www.ncbi.nlm.nih.gov/pubmed/32664599 http://dx.doi.org/10.3390/brainsci10070442 |
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