Multiclass classification of imagined speech EEG using noise-assisted multivariate empirical mode decomposition and multireceptive field convolutional neural network

Multiclass classification of imagined speech EEG using noise-assisted multivariate empirical mode decomposition and multireceptive field convolutional neural network

IntroductionIn this study, we classified electroencephalography (EEG) data of imagined speech using signal decomposition and multireceptive convolutional neural network. The imagined speech EEG with five vowels /a/, /e/, /i/, /o/, and /u/, and mute (rest) sounds were obtained from ten study particip...

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Bibliographic Details
Main Authors: Hyeong-jun Park, Boreom Lee
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-08-01
Series:Frontiers in Human Neuroscience
Subjects:
brain-computer interfaces
imagined speech EEG
multiclass classification
multireceptive field convolutional neural network
noise-assisted empirical mode decomposition
Online Access:https://www.frontiersin.org/articles/10.3389/fnhum.2023.1186594/full

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https://www.frontiersin.org/articles/10.3389/fnhum.2023.1186594/full

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