Results 321 to 330 of about 874,261 (376)

EEG-Based Emotion Recognition via Channel-Wise Attention and Self Attention

IEEE Transactions on Affective Computing, 2023
Emotion recognition based on electroencephalography (EEG) is a significant task in the brain-computer interface field. Recently, many deep learning-based emotion recognition methods are demonstrated to outperform traditional methods.
Wei Tao, Chang Li, Rencheng Song, Juan Cheng, Yu Liu, Feng Wan, Xun Chen   +6 more
semanticscholar   +1 more source

Physics-Informed Attention Temporal Convolutional Network for EEG-Based Motor Imagery Classification

IEEE Transactions on Industrial Informatics, 2023
The brain-computer interface (BCI) is a cutting-edge technology that has the potential to change the world. Electroencephalogram (EEG) motor imagery (MI) signal has been used extensively in many BCI applications to assist disabled people, control devices
Hamdi Altaheri, G. Muhammad, Mansour Alsulaiman   +2 more
semanticscholar   +1 more source

EEG Emotion Recognition Using Dynamical Graph Convolutional Neural Networks

IEEE Transactions on Affective Computing, 2020
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 EEG emotion recognition method is to use a graph to model the multichannel EEG
Tengfei Song, Wenming Zheng, Peng Song, Zhen Cui   +3 more
semanticscholar   +1 more source

EEG Essentials

Continuum, 2022
EEG is the best study for evaluating the electrophysiologic function of the brain. The relevance of EEG is based on an accurate interpretation of the recording. Understanding the neuroscientific basis for EEG is essential. The basis for recording and interpreting EEG is both brain site-specific and technique-dependent to detect and represent a complex ...
openaire   +2 more sources

Ambulatory EEG

2019
Ambulatory electroencephalography (aEEG) is a technique of continuous EEG recording while ensuring maximum mobility of the patient in a more naturalistic setting. The initial technological drawbacks of aEEG have been circumvented by incorporating digital and computer technology.
Udaya, Seneviratne, Wendyl Jude, D'Souza
openaire   +2 more sources

Adult EEG

2019
After more than 85 years of development and use in clinical practice, the electroencephalogram (EEG) remains a dependable, inexpensive, and useful diagnostic tool for the investigation of the electrophysiologic activity of the brain. The advent of digital technology has led to greater sophistication and multiple software applications to extend the ...
Anteneh M, Feyissa, William O, Tatum
openaire   +2 more sources

Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI

International Conference on Learning Representations
The current electroencephalogram (EEG) based deep learning models are typically designed for specific datasets and applications in brain-computer interaction (BCI), limiting the scale of the models and thus diminishing their perceptual capabilities and ...
Wei-Bang Jiang, Li-Ming Zhao, Bao-Liang Lu   +2 more
semanticscholar   +1 more source

EEG coherence or EEG correlation?

International Journal of Psychophysiology, 1996
In view of the widespread use of electroencephalographic correlation (r) and coherence (Coh) analyses in studying brain functional relationships, it seems important to illustrate results yielded by both methods. Although they are considered as equivalent, they show important differences.
M A, Guevara, M, Corsi-Cabrera
openaire   +2 more sources