8 citations
- Institute of Cognitive and Brain SciencesUS5 papers
- Korea UniversityKR3 papers
- Artificial Intelligence in Medicine (Canada)CA1 paper
- Berlin Institute for the Foundations of Learning and DataDE1 paper
- Berlin Institute of Health at Charité - Universitätsmedizin BerlinDE1 paper
- Catholic University of KoreaKR1 paper
- Charité - Universitätsmedizin BerlinDE1 paper
- ETH ZurichCH1 paper
- Hanyang UniversityKR1 paper
- Jeju National UniversityKR1 paper
- Max Planck Institute for InformaticsDE1 paper
- Miami UniversityUS1 paper
4 papers · 1 filter
Design of an EEG-based Drone Swarm Control System using Endogenous BCI Paradigms
Dae-Hyeok Lee, Hyung-Ju Ahn, Ji-Hoon Jeong +1
Non-invasive brain-computer interface (BCI) has been developed for understanding users' intentions by using electroencephalogram (EEG) signals. With the recent development of artif…
Functional Connectivity of Imagined Speech and Visual Imagery based on Spectral Dynamics
Seo-Hyun Lee, Minji Lee, Seong-Whan Lee
Recent advances in brain-computer interface technology have shown the potential of imagined speech and visual imagery as a robust paradigm for intuitive brain-computer interface co…
Automatic Micro-sleep Detection under Car-driving Simulation Environment using Night-sleep EEG
Young-Seok Kweon, Gi-Hwan Shin, Heon-Gyu Kwak +1
A micro-sleep is a short sleep that lasts from 1 to 30 secs. Its detection during driving is crucial to prevent accidents that could claim a lot of people's lives. Electroencephalo…
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…