Deep learning in motor imagery EEG signal decoding: A Systematic Review

A Saibene, H Ghaemi, E Dagdevir - Neurocomputing, 2024 - Elsevier
Thanks to the fast evolution of electroencephalography (EEG)-based brain-computer
interfaces (BCIs) and computing technologies, as well as the availability of large EEG …

Mental imagery classification using one-dimensional convolutional neural network for target selection in single-channel BCI-controlled mobile robot

TA Izzuddin, NM Safri, MA Othman - Neural Computing and Applications, 2021 - Springer
This paper introduces the use of the one-dimensional convolutional neural network (1D-
CNN) for end-to-end EEG decoding with application towards a BCI system with a shared …

Hybrid brain-computer interface with motor imagery and error-related brain activity

M Mousavi, LR Krol, VR de Sa - Journal of Neural Engineering, 2020 - iopscience.iop.org
Objective. Brain-computer interface (BCI) systems read and interpret brain activity directly
from the brain. They can provide a means of communication or locomotion for patients …

Spectrally adaptive common spatial patterns

M Mousavi, E Lybrand, S Feng, S Tang, R Saab… - arxiv preprint arxiv …, 2022 - arxiv.org
The method of Common Spatial Patterns (CSP) is widely used for feature extraction of
electroencephalography (EEG) data, such as in motor imagery brain-computer interface …

A Convolutional Network Adaptation for Cortical Classification During Mobile Brain Imaging

B Cichy, J Lukos, M Alam, JC Bradford… - arxiv preprint arxiv …, 2023 - arxiv.org
Deep neural networks (DNN) have become increasingly utilized in brain-computer interface
(BCI) technologies with the outset goal of classifying human physiological signals in …

Perception estimation and torque control for hand prostheses using EEG and EMG signals

N Karakullukcu - 2024 - acikerisim.agu.edu.tr
Upper extremity prostheses vary based on patients' articulation levels and movement
methods. They can be cosmetic, operate mechanically with shoulder movement, or be …

[PDF][PDF] Compact and interpretable convolutional neural network architecture for electroencephalogram based motor imagery decoding

TA IZZUDDIN - 2022 - eprints.utm.my
Recently, due to the popularity of deep learning, the applicability of deep Neural Networks
(DNN) algorithms such as the convolutional neural networks (CNN) has been explored in …

[PDF][PDF] Федеральное государственное бюджетное учреждение науки Институт общей физики им. АМ Прохорова Российской академии наук

АА Ушаков - Москва, 2019 - diss.gpi.ru
Под терагерцевым (ТГц) понимают электромагнитное излучение в диапазоне частот
0.1–10 ТГц (или в диапазоне длин волн 3 мм–30 мкм), которое располагается между …