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 …

In this study, we conducted a systematic literature review of 107 primary studies conducted
between 2017 and 2023 to discern trends in datasets, classifiers, and contributions to …

Imbalanced datasets pose significant challenges in areas including neuroscience, cognitive
science, and medical diagnostics, where accurately detecting minority classes is essential …

The main objective of this paper is to highlight the research directions and explain the main
roles of current Artificial Intelligence (AI)/Machine Learning (ML) frameworks and available …

Introduction Efficiently recognizing emotions is a critical pursuit in brain–computer interface
(BCI), as it has many applications for intelligent healthcare services. In this work, an …

Background In the last decade, long-tail learning has become a popular research focus in
deep learning applications in medicine. However, no scientometric reports have provided a …

Emotion Recognition through electroencephalography (EEG) is one of the prevailing
emotion recognition techniques achieving higher accuracy rates. Nevertheless, one of the …

Introduction Affective computing is the core for Human-computer interface (HCI) to be more
intelligent, where electroencephalogram (EEG) based emotion recognition is one of the …

Background: Decoding emotions from brain maps is a challenging task. Convolutional
Neural Network (CNN) is commonly used for EEG feature map. However, due to its local …

Electroencephalogram (EEG) channel optimization can reduce redundant information and
improve EEG decoding accuracy by selecting the most informative channels. This article …