Emotion recognition is the ability to precisely infer human emotions from numerous sources
and modalities using questionnaires, physical signals, and physiological signals. Recently …

Emotion recognition technology through analyzing the EEG signal is currently an essential
concept in Artificial Intelligence and holds great potential in emotional health care, human …

Given the rapid development of brain–computer interfaces, emotion identification based on
EEG signals has emerged as a new study area with tremendous importance in recent years …

Emotions are a critical aspect of daily life and serve a crucial role in human decision-making,
planning, reasoning, and other mental states. As a result, they are considered a significant …

Construction workers' cognitive statuses affecting their safety and productivity are essential
for successful construction management. Electroencephalogram (EEG) provides a potential …

EEG signals have been reported to be informative and reliable for emotion recognition in
recent years. However, the inter-subject variability of emotion-related EEG signals still poses …

Deep learning (DL) technologies have recently shown great potential in emotion recognition
based on electroencephalography (EEG). However, existing DL-based EEG emotion …

Emotion recognition using electroencephalogram (EEG) signals is getting more and more
attention in recent years. Since the EEG signals are noisy, non-linear and have non …

Deep learning has recently achieved remarkable success in emotion recognition based on
Electroencephalogram (EEG), in which convolutional neural networks (CNNs) are the mostly …

The spatial information of Electroencephalography (EEG) is essential for emotion
recognition model to learn discriminative feature. The convolutional networks and recurrent …