Deep learning in EEG-based BCIs: a comprehensive review of transformer models, advantages, challenges, and applications
Brain-computer interfaces (BCIs) have undergone significant advancements in recent years.
The integration of deep learning techniques, specifically transformers, has shown promising …
The integration of deep learning techniques, specifically transformers, has shown promising …
Traumatic brain injury (TBI) detection: past, present, and future
AT Alouani, T Elfouly - Biomedicines, 2022 - mdpi.com
Traumatic brain injury (TBI) can produce temporary biochemical imbalance due to leaks
through cell membranes or disruption of the axoplasmic flow due to the misalignment of …
through cell membranes or disruption of the axoplasmic flow due to the misalignment of …
Eeg-based alzheimer's disease recognition using robust-pca and lstm recurrent neural network
M Alessandrini, G Biagetti, P Crippa, L Falaschetti… - Sensors, 2022 - mdpi.com
The use of electroencephalography (EEG) has recently grown as a means to diagnose
neurodegenerative pathologies such as Alzheimer's disease (AD). AD recognition can …
neurodegenerative pathologies such as Alzheimer's disease (AD). AD recognition can …
Joint feature adaptation and graph adaptive label propagation for cross-subject emotion recognition from EEG signals
Though Electroencephalogram (EEG) could objectively reflect emotional states of our
human beings, its weak, non-stationary, and low signal-to-noise properties easily cause the …
human beings, its weak, non-stationary, and low signal-to-noise properties easily cause the …
Semi-supervised EEG emotion recognition model based on enhanced graph fusion and GCN
Objective. To take full advantage of both labeled data and unlabeled ones, the Graph
Convolutional Network (GCN) was introduced in electroencephalography (EEG) based …
Convolutional Network (GCN) was introduced in electroencephalography (EEG) based …
Deep convolutional neural network regularization for alcoholism detection using EEG signals
Alcoholism is attributed to regular or excessive drinking of alcohol and leads to the
disturbance of the neuronal system in the human brain. This results in certain malfunctioning …
disturbance of the neuronal system in the human brain. This results in certain malfunctioning …
An auto-weighting incremental random vector functional link network for EEG-based driving fatigue detection
Recently, electroencephalogram (EEG) has been receiving increasing attention in driving
fatigue attention because it is generated by the neural activities of central nervous system …
fatigue attention because it is generated by the neural activities of central nervous system …
A channel independent generalized seizure detection method for pediatric epileptic seizures
Background and objective Epilepsy the disorder of the central nervous system has its
worldwide presence in roughly 50 million people as estimated by the World Health …
worldwide presence in roughly 50 million people as estimated by the World Health …
Self-weighted semi-supervised classification for joint EEG-based emotion recognition and affective activation patterns mining
In electroencephalography (EEG)-based affective brain–computer interfaces (aBCIs), there
is a consensus that EEG features extracted from different frequency bands and channels …
is a consensus that EEG features extracted from different frequency bands and channels …
[HTML][HTML] Graph adaptive semi-supervised discriminative subspace learning for EEG emotion recognition
Since Electroencephalogram (EEG) is resistant to camouflage and contains abundant
neurophysiological information, it shows significant superiorities in objective emotion …
neurophysiological information, it shows significant superiorities in objective emotion …