2020 International brain–computer interface competition: A review
The brain-computer interface (BCI) has been investigated as a form of communication tool
between the brain and external devices. BCIs have been extended beyond communication …
between the brain and external devices. BCIs have been extended beyond communication …
Review of public motor imagery and execution datasets in brain-computer interfaces
The demand for public datasets has increased as data-driven methodologies have been
introduced in the field of brain-computer interfaces (BCIs). Indeed, many BCI datasets are …
introduced in the field of brain-computer interfaces (BCIs). Indeed, many BCI datasets are …
NeuroGrasp: Real-time EEG classification of high-level motor imagery tasks using a dual-stage deep learning framework
Brain–computer interfaces (BCIs) have been widely employed to identify and estimate a
user's intention to trigger a robotic device by decoding motor imagery (MI) from an …
user's intention to trigger a robotic device by decoding motor imagery (MI) from an …
EEGANet: Removal of ocular artifacts from the EEG signal using generative adversarial networks
P Sawangjai, M Trakulruangroj… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
The elimination of ocular artifacts is critical in analyzing electroencephalography (EEG) data
for various brain-computer interface (BCI) applications. Despite numerous promising …
for various brain-computer interface (BCI) applications. Despite numerous promising …
FBMSNet: A filter-bank multi-scale convolutional neural network for EEG-based motor imagery decoding
K Liu, M Yang, Z Yu, G Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Object: Motor imagery (MI) is a mental process widely utilized as the experimental paradigm
for brain-computer interfaces (BCIs) across a broad range of basic science and clinical …
for brain-computer interfaces (BCIs) across a broad range of basic science and clinical …
Real-time deep neurolinguistic learning enhances noninvasive neural language decoding for brain–machine interaction
Electroencephalogram (EEG)-based brain–machine interface (BMI) has been utilized to
help patients regain motor function and has recently been validated for its use in healthy …
help patients regain motor function and has recently been validated for its use in healthy …
Motor imagery classification using inter-task transfer learning via a channel-wise variational autoencoder-based convolutional neural network
Highly sophisticated control based on a brain-computer interface (BCI) requires decoding
kinematic information from brain signals. The forearm is a region of the upper limb that is …
kinematic information from brain signals. The forearm is a region of the upper limb that is …
DL-AMPUT-EEG: Design and development of the low-cost prosthesis for rehabilitation of upper limb amputees using deep-learning-based techniques
Upper limb amputation is a widespread problem worldwide, leading to massive loss of
functionality for the victims. While a few solutions exist, these are often very expensive and …
functionality for the victims. While a few solutions exist, these are often very expensive and …
[HTML][HTML] M3CV: A multi-subject, multi-session, and multi-task database for EEG-based biometrics challenge
EEG signals exhibit commonality and variability across subjects, sessions, and tasks. But
most existing EEG studies focus on mean group effects (commonality) by averaging signals …
most existing EEG studies focus on mean group effects (commonality) by averaging signals …
Design of an EEG-based drone swarm control system using endogenous BCI paradigms
Non-invasive brain-computer interface (BCI) has been developed for understanding users'
intentions by using electroencephalogram (EEG) signals. With the recent development of …
intentions by using electroencephalogram (EEG) signals. With the recent development of …