1 citations · 3 across the 7 of their papers we have counts for
7 papers
Target-centered Subject Transfer Framework for EEG Data Augmentation
Kang Yin, Byeong-Hoo Lee, Byoung-Hee Kwon +1
Data augmentation approaches are widely explored for the enhancement of decoding electroencephalogram signals. In subject-independent brain-computer interface system, domain adapti…
Channel Optimized Visual Imagery based Robotic Arm Control under the Online Environment
Byoung-Hee Kwon, Byeong-Hoo Lee, Jeong-Hyun Cho
An electroencephalogram is an effective approach that provides a bidirectional pathway between the user and computer in a non-invasive way. In this study, we adopted the visual ima…
Towards Neurohaptics: Brain-Computer Interfaces for Decoding Intuitive Sense of Touch
Jeong-Hyun Cho, Ji-Hoon Jeong, Myoung-Ki Kim +1
Noninvasive brain-computer interface (BCI) is widely used to recognize users' intentions. Especially, BCI related to tactile and sensation decoding could provide various effects on…
Classification of Tactile Perception and Attention on Natural Textures from EEG Signals
Myoung-Ki Kim, Jeong-Hyun Cho, Ji-Hoon Jeong
Brain-computer interface allows people who have lost their motor skills to control robot limbs based on electroencephalography. Most BCIs are guided only by visual feedback and do…
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…
Decoding of Grasp Motions from EEG Signals Based on a Novel Data Augmentation Strategy
Jeong-Hyun Cho, Ji-Hoon Jeong, Seong-Whan Lee
Electroencephalogram (EEG) based brain-computer interface (BCI) systems are useful tools for clinical purposes like neural prostheses. In this study, we collected EEG signals relat…