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 …
MS-MDA: Multisource marginal distribution adaptation for cross-subject and cross-session EEG emotion recognition
As an essential element for the diagnosis and rehabilitation of psychiatric disorders, the
electroencephalogram (EEG) based emotion recognition has achieved significant progress …
electroencephalogram (EEG) based emotion recognition has achieved significant progress …
Neural decoding of imagined speech and visual imagery as intuitive paradigms for BCI communication
SH Lee, M Lee, SW Lee - IEEE Transactions on Neural …, 2020 - ieeexplore.ieee.org
Brain-computer interface (BCI) is oriented toward intuitive systems that users can easily
operate. Imagined speech and visual imagery are emerging paradigms that can directly …
operate. Imagined speech and visual imagery are emerging paradigms that can directly …
[HTML][HTML] Opportunities, pitfalls and trade-offs in designing protocols for measuring the neural correlates of speech
Decoding speech and speech-related processes directly from the human brain has
intensified in studies over recent years as such a decoder has the potential to positively …
intensified in studies over recent years as such a decoder has the potential to positively …
Machine-learning-enabled adaptive signal decomposition for a brain-computer interface using EEG
Background and objective The use of adaptive signal decomposition methods and machine
learning (ML) algorithms have gained interest in biomedical applications. Brain-computer …
learning (ML) algorithms have gained interest in biomedical applications. Brain-computer …
EEG-transformer: Self-attention from transformer architecture for decoding EEG of imagined speech
YE Lee, SH Lee - 2022 10th International winter conference on …, 2022 - ieeexplore.ieee.org
Transformers are groundbreaking architectures that have changed a flow of deep learning,
and many high-performance models are developing based on transformer architectures …
and many high-performance models are developing based on transformer architectures …
Deep-learning-based BCI for automatic imagined speech recognition using SPWVD
The electroencephalogram (EEG)-based brain–computer interface (BCI) has potential
applications in neuroscience and rehabilitation. It benefits a person with neurological …
applications in neuroscience and rehabilitation. It benefits a person with neurological …
Classifying students based on cognitive state in flipped learning pedagogy
The flipped learning (FL) is found to be an effective teaching methodology which is
accomplished in two stages. In the first stage, students take instructions and learn from pre …
accomplished in two stages. In the first stage, students take instructions and learn from pre …
Decoding imagined speech based on deep metric learning for intuitive BCI communication
DY Lee, M Lee, SW Lee - IEEE Transactions on Neural …, 2021 - ieeexplore.ieee.org
Imagined speech is a highly promising paradigm due to its intuitive application and
multiclass scalability in the field of brain-computer interfaces. However, optimal feature …
multiclass scalability in the field of brain-computer interfaces. However, optimal feature …
The LightGBM-based classification algorithm for Chinese characters speech imagery BCI system
H Pan, Z Li, C Tian, L Wang, Y Fu, X Qin, F Liu - Cognitive Neurodynamics, 2023 - Springer
Brain–computer interface (BCI) can obtain text information by decoding language induced
electroencephalogram (EEG) signals, so as to restore communication ability for patients with …
electroencephalogram (EEG) signals, so as to restore communication ability for patients with …