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 …

An electroencephalography (EEG)-based brain–computer interface (BCI) is a system that
provides a pathway between the brain and external devices by interpreting EEG. EEG …

In this paper, we present a multimodal emotion recognition framework called EmotionMeter
that combines brain waves and eye movements. To increase the feasibility and wearability …

The electroencephalography (EEG) sensor has become a prominent sensor in the study of
brain activity. Its applications extend from research studies to medical applications. This …

To investigate critical frequency bands and channels, this paper introduces deep belief
networks (DBNs) to constructing EEG-based emotion recognition models for three emotions …

This study aimed to construct a novel multimodal model by fusing different
electroencephalogram (EEG) data sources, which were under neutral, negative and positive …

Emotion recognition based on electroencephalography (EEG) signal features is now one of
the booming big data research areas. As the number of commercial EEG devices in the …

To enhance the performance of affective models and reduce the cost of acquiring
physiological signals for real-world applications, we adopt multimodal deep learning …

Emotions play an important role in the learning process. Considering the learner's emotions
is essential for electronic learning (e-learning) systems. Some researchers have proposed …

The application of biometric data has been the center of attention for neuromarketing
researches. Understanding the underlying mechanisms behind consumer shopping …