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

Assessment of the cognitive functions and state of clinical subjects is an important aspect of
e-health care delivery, and in the development of novel human-machine interfaces. A …

Background: Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental
disorder that affects a person's sleep, mood, anxiety, and learning. Early diagnosis and …

Emotion recognition using electroencephalography (EEG) is becoming an interesting topic
among researchers. It has made a remarkable entry in the domain of biomedical, smart …

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

Schizophrenia (SZ) is a psychiatric disorder characterized by cognitive dysfunctions,
hallucinations, and delusions, which may lead to lifetime disability. Detection and diagnosis …

Abstract Brain-Computer Interaction (BCI) system intelligence has become more dependent
on electroencephalogram (EEG)-based emotion recognition because of the numerous …

Machine learning (ML)-based algorithms have shown promising results in
electroencephalogram (EEG)-based emotion recognition. This study compares five …

Signal processing techniques play an important role in seismic data analysis. Variational
mode decomposition (VMD), as a powerful signal processing method, has been extensively …

Emotions are viewed as an important aspect of human interactions and conversations, and
allow effective and logical decision making. Emotion recognition uses low-cost wearable …