A Deep Learning Framework for Decoding Motor Imagery Tasks of the Same Hand Using EEG Signals

A Deep Learning Framework for Decoding Motor Imagery Tasks of the Same Hand Using EEG Signals

This study aims to increase the control's dimensions of the electroencephalography (EEG)-based brain-computer interface (BCI) systems by distinguishing between the motor imagery (MI) tasks associated with fine body-parts of the same hand, such as the wrist and fingers. This in turn can enable i...

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Bibliographic Details
Main Authors: Rami Alazrai, Motaz Abuhijleh, Hisham Alwanni, Mohammad I. Daoud
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Convolutional neural networks (CNN)
deep learning
electroencephalography (EEG)
motor imagery
time-frequency distribution
Online Access:https://ieeexplore.ieee.org/document/8792041/

Internet

https://ieeexplore.ieee.org/document/8792041/

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