Recently, electroencephalogram-based emotion recognition has become crucial in enabling
the Human-Computer Interaction (HCI) system to become more intelligent. Due to the …

Among various physiological signal acquisition methods for the study of the human brain,
EEG (Electroencephalography) is more effective. EEG provides a convenient, non-intrusive …

Epilepsy is a disease caused by abnormal discharges in the central nervous system.
Automatic detection and accurate identification of epileptic seizures based on …

This study is based on EEG brain wave classification of a well-known dataset called the EEG
Brainwave Dataset. The dataset combines three classes such as positive, negative, and …

Facial emotion recognition is one of the most important subjects in image processing and
computer vision fields. Through facial emotions the interaction human-machine can get …

INTRODUCTION: Employee burnout is a prevalent concern in contemporary workplaces,
adversely impacting both individual well-being and organizational productivity …

The aim of this study is to investigate mental fatigue using the Kaplan-Meier and Nelson-
Aalen estimators in survival analysis. Mental fatigue is a common occurrence when the mind …

Extracting features from electroencephalogram (EEG) is a challenging task because the
signals are complex and chaotic in nature. EEG signals are time varying as human brain …

Emotions play an essential role in humans. It exerts influence on their decision-making,
reasoning, and behaviour. Human emotional responses to any kind of stimuli are commonly …

The effectiveness of wireless electroencephalograph (EEG) sensor-based medical or Brain
Computer Interface applications largely depends on how to classify EEG signals as …