Zobrazeno 1 - 10
of 234
pro vyhledávání: '"Cho, Jeong‐Hyun"'
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 motor execution (ME) and motor imagery (MI). During this experiment, eig
Externí odkaz:
http://arxiv.org/abs/2212.07083
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 robotic arm. In this study, we propose a knowledge distillation-based framew
Externí odkaz:
http://arxiv.org/abs/2212.08122
Data augmentation approaches are widely explored for the enhancement of decoding electroencephalogram signals. In subject-independent brain-computer interface system, domain adaption and generalization are utilized to shift source subjects' data dist
Externí odkaz:
http://arxiv.org/abs/2212.00723
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 imagery data for controlling the BCI-based robotic arm. Visual imagery in
Externí odkaz:
http://arxiv.org/abs/2211.13366
Recently, advanced technologies have unlimited potential in solving various problems with a large amount of data. However, these technologies have yet to show competitive performance in brain-computer interfaces (BCIs) which deal with brain signals.
Externí odkaz:
http://arxiv.org/abs/2206.08494
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. However, developing a BCI system driven by ME or MI is challenging, p
Externí odkaz:
http://arxiv.org/abs/2112.07943
Touch is the first sense among human senses. Not only that, but it is also one of the most important senses that are indispensable. However, compared to sight and hearing, it is often neglected. In particular, since humans use the tactile sense of th
Externí odkaz:
http://arxiv.org/abs/2112.07123
Brain-computer interface uses brain signals to communicate with external devices without actual control. Many studies have been conducted to classify motor imagery based on machine learning. However, classifying imagery data with sparse spatial chara
Externí odkaz:
http://arxiv.org/abs/2112.08175
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 perception data for training the visual imagery decoding network. We proposed
Externí odkaz:
http://arxiv.org/abs/2112.06429
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 many industrial fields such as manufacturing advanced touch displays,
Externí odkaz:
http://arxiv.org/abs/2012.06753