128 citations · 396 across the 49 of their papers we have counts for
8 papers · 1 filter
DAL: Feature Learning from Overt Speech to Decode Imagined Speech-based EEG Signals with Convolutional Autoencoder
Dae-Hyeok Lee, Sung-Jin Kim, Seong-Whan Lee
Brain-computer interface (BCI) is one of the tools which enables the communication between humans and devices by reflecting intention and status of humans. With the development of…
Decoding Visual Recognition of Objects from EEG Signals based on Attention-Driven Convolutional Neural Network
Jenifer Kalafatovich, Minji Lee, Seong-Whan Lee
The ability to perceive and recognize objects is fundamental for the interaction with the external environment. Studies that investigate them and their relationship with brain acti…
Classification of Imagined Speech Using Siamese Neural Network
Dong-Yeon Lee, Minji Lee, Seong-Whan Lee
Imagined speech is spotlighted as a new trend in the brain-machine interface due to its application as an intuitive communication tool. However, previous studies have shown low cla…
Reconstructing ERP Signals Using Generative Adversarial Networks for Mobile Brain-Machine Interface
Young-Eun Lee, Minji Lee, Seong-Whan Lee
Practical brain-machine interfaces have been widely studied to accurately detect human intentions using brain signals in the real world. However, the electroencephalography (EEG) s…
Decoding of Intuitive Visual Motion Imagery Using Convolutional Neural Network under 3D-BCI Training Environment
Byoung-Hee Kwon, Ji-Hoon Jeong, Jeong-Hyun Cho +1
In this study, we adopted visual motion imagery, which is a more intuitive brain-computer interface (BCI) paradigm, for decoding the intuitive user intention. We developed a 3-dime…
Assessment of Unconsciousness for Memory Consolidation Using EEG Signals
Gi-Hwan Shin, Minji Lee, Seong-Whan Lee
The assessment of consciousness and unconsciousness is a challenging issue in modern neuroscience. Consciousness is closely related to memory consolidation in that memory is a crit…
Prediction of Memory Retrieval Performance Using Ear-EEG Signals
Jenifer Kalafatovich, Minji Lee, Seong-Whan Lee
Many studies have explored brain signals during the performance of a memory task to predict later remembered items. However, prediction methods are still poorly used in real life a…
Classification of High-Dimensional Motor Imagery Tasks based on An End-to-end role assigned convolutional neural network
Byeong-Hoo Lee, Ji-Hoon Jeong, Kyung-Hwan Shim +1
A brain-computer interface (BCI) provides a direct communication pathway between user and external devices. Electroencephalogram (EEG) motor imagery (MI) paradigm is widely used in…