8 papers · 1 filter
Hybrid Paradigm-based Brain-Computer Interface for Robotic Arm Control
Byeong-Hoo Lee, Jeong-Hyun Cho, Byung-Hee Kwon
Brain-computer interface (BCI) uses brain signals to communicate with external devices without actual control. Particularly, BCI is one of the interfaces for controlling the roboti…
Decoding Multi-class Motor-related Intentions with User-optimized and Robust BCI System Based on Multimodal Dataset
Jeong-Hyun Cho, Byoung-Hee Kwon, Byeong-Hoo Lee
A brain-computer interface (BCI) based on electroencephalography (EEG) can be useful for rehabilitation and the control of external devices. Five grasping tasks were decoded for mo…
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…
Decoding Continual Muscle Movements Related to Complex Hand Grasping from EEG Signals
Jeong-Hyun Cho, Byoung-Hee Kwon, Byeong-Hoo Lee +1
Brain-computer interface (BCI) is a practical pathway to interpret users' intentions by decoding motor execution (ME) or motor imagery (MI) from electroencephalogram (EEG) signals.…
Decoding Visual Imagery from EEG Signals using Visual Perception Guided Network Training Method
Byoung-Hee Kwon, Jeong-Hyun Cho, Byeong-Hoo Lee
An electroencephalogram is an effective approach that provides a bidirectional pathway between user and computer in a non-invasive way. In this study, we adopted the visual percept…
Speech Imagery Classification using Length-Wise Training based on Deep Learning
Byeong-Hoo Lee, Byeong-Hee Kwon, Do-Yeun Lee +1
Brain-computer interface uses brain signals to control external devices without actual control behavior. Recently, speech imagery has been studied for direct communication using la…
Motor Imagery Classification Emphasizing Corresponding Frequency Domain Method based on Deep Learning Framework
Byoung-Hee Kwon, Byeong-Hoo Lee, Ji-Hoon Jeong
The electroencephalogram, a type of non-invasive-based brain signal that has a user intention-related feature provides an efficient bidirectional pathway between user and computer.…
Motor Imagery Classification of Single-Arm Tasks Using Convolutional Neural Network based on Feature Refining
Byeong-Hoo Lee, Ji-Hoon Jeong, Kyung-Hwan Shim +1
Brain-computer interface (BCI) decodes brain signals to understand user intention and status. Because of its simple and safe data acquisition process, electroencephalogram (EEG) is…