A survey on deep learning-based short/zero-calibration approaches for EEG-based brain–computer interfaces
Brain–computer interfaces (BCIs) utilizing machine learning techniques are an emerging
technology that enables a communication pathway between a user and an external system …
technology that enables a communication pathway between a user and an external system …
Data augmentation for motor imagery signal classification based on a hybrid neural network
As an important paradigm of spontaneous brain-computer interfaces (BCIs), motor imagery
(MI) has been widely used in the fields of neurological rehabilitation and robot control …
(MI) has been widely used in the fields of neurological rehabilitation and robot control …
Learning invariant representations from EEG via adversarial inference
Discovering and exploiting shared, invariant neural activity in electroencephalogram (EEG)
based classification tasks is of significant interest for generalizability of decoding models …
based classification tasks is of significant interest for generalizability of decoding models …
Motor imagery signal classification using adversarial learning: A systematic literature review
S Mishra, O Mahmudi, A Jalali - IEEE Access, 2024 - ieeexplore.ieee.org
This paper presents a comprehensive Systematic Literature Review (SLR) on the utilization
of adversarial learning techniques in Motor Imagery (MI) signal classification, a key …
of adversarial learning techniques in Motor Imagery (MI) signal classification, a key …
Multi-source transfer learning for EEG classification based on domain adversarial neural network
Electroencephalogram (EEG) classification has attracted great attention in recent years, and
many models have been presented for this task. Nevertheless, EEG data vary from subject to …
many models have been presented for this task. Nevertheless, EEG data vary from subject to …
Generation of synthetic EEG data for training algorithms supporting the diagnosis of major depressive disorder
FP Carrle, Y Hollenbenders… - Frontiers in Neuroscience, 2023 - frontiersin.org
Introduction Major depressive disorder (MDD) is the most common mental disorder
worldwide, leading to impairment in quality and independence of life …
worldwide, leading to impairment in quality and independence of life …
A conditional input-based GAN for generating spatio-temporal motor imagery electroencephalograph data
Abstract Brain Computer Interface is an emerging technology for assisting patients having
long term disability. Electroencephalography is the best technique for recording neural …
long term disability. Electroencephalography is the best technique for recording neural …
Semi-supervised generative and discriminative adversarial learning for motor imagery-based brain–computer interface
Convolutional neural networks (CNNs), which can recognize structural/configuration
patterns in data with different architectures, have been studied for feature extraction …
patterns in data with different architectures, have been studied for feature extraction …
Human-robot collaborative disassembly enabled by brainwaves and improved generative adversarial network
Human-robot collaboration (HRC) can greatly facilitate the disassembling processes of end-
of-life (EoL) products. For the robot in HRC, an intuitive control function enabled by a brain …
of-life (EoL) products. For the robot in HRC, an intuitive control function enabled by a brain …
Stimulus-independent noninvasive BCI based on EEG patterns of inner speech
VN Kiroy, EV Aslanyan, OM Bakhtin, EM Krivko… - Brain-Computer …, 2025 - Elsevier
Multiple studies have concerned electrographic correlates and neurophysiological
mechanisms of speech. Despite this, the question remains whether speech content is …
mechanisms of speech. Despite this, the question remains whether speech content is …