Motor Imagery EEG Recognition using Deep Generative Adversarial Network with EMD for BCI Applications

Motor Imagery EEG Recognition using Deep Generative Adversarial Network with EMD for BCI Applications

The activities for motor imagery (MI) movements in Electroencephalography (EEG) are still interesting and challenging. BCI (Brain Computer Interface) allows the brain signals to control the external devices and also helps a disabled person suffering from neuromuscular disorders. In any BCI system, t...

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Bibliographic Details
Main Authors: Stephan Stephe, Thangaiyan Jayasankar*, Kalimuthu Vinoth Kumar
Format: Article
Language:English
Published: Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek 2022-01-01
Series:Tehnički Vjesnik
Subjects:
convolutional neural network (CNN)
electroencephalogram (EEG)
empirical mode decomposition (EMD)
generative adversarial network (GAN)
intrinsic mode function (IMF)
motor imagery (MI)
Online Access:https://hrcak.srce.hr/file/390873

Internet

https://hrcak.srce.hr/file/390873

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