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 …

The emergence of artificial emotional intelligence technology is revolutionizing the fields of
computers and robotics, allowing for a new level of communication and understanding of …

In recent years, affective computing has become a topic of considerable interest, driven by
its ability to enhance several domains, such as mental health monitoring, human–computer …

How to extract discriminative latent feature representations from electroencephalography
(EEG) signals and build a generalized model is a topic in EEG-based emotion recognition …

Human dependence on computers is increasing day by day; thus, human interaction with
computers must be more dynamic and contextual rather than static or generalized. The …

Goal: As an essential human-machine interactive task, emotion recognition has become an
emerging area over the decades. Although previous attempts to classify emotions have …

Physiological signals are the most reliable form of signals for emotion recognition, as they
cannot be controlled deliberately by the subject. Existing review papers on emotion …

Most emotion recognition systems still present limited applicability to new users due to the
intersubject variability of electroencephalogram (EEG) signals. Although domain adaptation …

A growing number of individuals are expressing their opinions and engaging in interactive
communication with others through various modalities, including natural language (text) …

The use of machine learning (ML) techniques in affective computing applications focuses on
improving the user experience in emotion recognition. The collection of input data (eg …