Imaginary Finger Movements Decoding Using Empirical Mode Decomposition and a Stacked BiLSTM Architecture

Imaginary Finger Movements Decoding Using Empirical Mode Decomposition and a Stacked BiLSTM Architecture

Motor Imagery Electroencephalogram (MI-EEG) signals are widely used in Brain-Computer Interfaces (BCI). MI-EEG signals of large limbs movements have been explored in recent researches because they deliver relevant classification rates for BCI systems. However, smaller and noisy signals corresponding...

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Bibliographic Details
Main Authors:	Tat’y Mwata-Velu, Juan Gabriel Avina-Cervantes, Jorge Mario Cruz-Duarte, Horacio Rostro-Gonzalez, Jose Ruiz-Pinales
Format:	Article
Language:	English
Published:	MDPI AG 2021-12-01
Series:	Mathematics
Subjects:	Electroencephalogram (EEG) Motor Imagery (MI) Empirical Mode Decomposition (EMD) Bidirectional Long Short-Term Memory (BiLSTM)
Online Access:	https://www.mdpi.com/2227-7390/9/24/3297

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