Decoding the User’s Movements Preparation From EEG Signals Using Vision Transformer Architecture

Decoding the User’s Movements Preparation From EEG Signals Using Vision Transformer Architecture

Electroencephalography (EEG) signals have a major impact on how well assistive rehabilitation devices work. These signals have become a common technique in recent studies to investigate human motion functions and behaviors. However, incorporating EEG signals to investigate motor planning or movement...

Full description

Bibliographic Details
Main Authors: Maged S. Al-Quraishi, Irraivan Elamvazuthi, Tong Boon Tang, Muhammad S. Al-Qurishi, Syed Hasan Adil, Mansoor Ebrahim, Alberto Borboni
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Continuous wavelet transform
deep learning
electroencephalography
motor-related cortical potentials
vision transformers architecture
Online Access:https://ieeexplore.ieee.org/document/9916262/

Internet

https://ieeexplore.ieee.org/document/9916262/

Similar Items