[HTML][HTML] Wireless EEG: A survey of systems and studies
The popular brain monitoring method of electroencephalography (EEG) has seen a surge in
commercial attention in recent years, focusing mostly on hardware miniaturization. This has …
commercial attention in recent years, focusing mostly on hardware miniaturization. This has …
Summary of over fifty years with brain-computer interfaces—a review
Over the last few decades, the Brain-Computer Interfaces have been gradually making their
way to the epicenter of scientific interest. Many scientists from all around the world have …
way to the epicenter of scientific interest. Many scientists from all around the world have …
EEG emotion recognition using dynamical graph convolutional neural networks
In this paper, a multichannel EEG emotion recognition method based on a novel dynamical
graph convolutional neural networks (DGCNN) is proposed. The basic idea of the proposed …
graph convolutional neural networks (DGCNN) is proposed. The basic idea of the proposed …
EEG-based spatio–temporal convolutional neural network for driver fatigue evaluation
Driver fatigue evaluation is of great importance for traffic safety and many intricate factors
would exacerbate the difficulty. In this paper, based on the spatial-temporal structure of …
would exacerbate the difficulty. In this paper, based on the spatial-temporal structure of …
An efficient LSTM network for emotion recognition from multichannel EEG signals
Most previous EEG-based emotion recognition methods studied hand-crafted EEG features
extracted from different electrodes. In this article, we study the relation among different EEG …
extracted from different electrodes. In this article, we study the relation among different EEG …
Investigating critical frequency bands and channels for EEG-based emotion recognition with deep neural networks
To investigate critical frequency bands and channels, this paper introduces deep belief
networks (DBNs) to constructing EEG-based emotion recognition models for three emotions …
networks (DBNs) to constructing EEG-based emotion recognition models for three emotions …
Brain computer interface: control signals review
RA Ramadan, AV Vasilakos - Neurocomputing, 2017 - Elsevier
Abstract Brain Computer Interface (BCI) is defined as a combination of hardware and
software that allows brain activities to control external devices or even computers. The …
software that allows brain activities to control external devices or even computers. The …
[HTML][HTML] Progress in brain computer interface: Challenges and opportunities
Brain computer interfaces (BCI) provide a direct communication link between the brain and a
computer or other external devices. They offer an extended degree of freedom either by …
computer or other external devices. They offer an extended degree of freedom either by …
EEG-based emotion classification using a deep neural network and sparse autoencoder
Emotion classification based on brain–computer interface (BCI) systems is an appealing
research topic. Recently, deep learning has been employed for the emotion classifications of …
research topic. Recently, deep learning has been employed for the emotion classifications of …
Review of semi-dry electrodes for EEG recording
GL Li, JT Wu, YH Xia, QG He… - Journal of Neural …, 2020 - iopscience.iop.org
Developing reliable and user-friendly electroencephalography (EEG) electrodes remains a
challenge for emerging real-world EEG applications. Classic wet electrodes are the gold …
challenge for emerging real-world EEG applications. Classic wet electrodes are the gold …