Recognition of human emotions using EEG signals: A review
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 …
e-health care delivery, and in the development of novel human-machine interfaces. A …
Recent progress in wearable brain–computer interface (BCI) devices based on electroencephalogram (EEG) for medical applications: a review
J Zhang, J Li, Z Huang, D Huang, H Yu, Z Li - Health Data Science, 2023 - spj.science.org
Importance: Brain–computer interface (BCI) decodes and converts brain signals into
machine instructions to interoperate with the external world. However, limited by the …
machine instructions to interoperate with the external world. However, limited by the …
EEG-based emotion analysis using non-linear features and ensemble learning approaches
Recognition of emotions based on electroencephalography (EEG) has become one of the
most emerging topics for healthcare, education system, knowledge sharing, gaming, and …
most emerging topics for healthcare, education system, knowledge sharing, gaming, and …
A hybrid neuro-experimental decision support system to classify overconfidence and performance in a simulated bubble using a passive BCI
FM Toma - Expert Systems with Applications, 2023 - Elsevier
Significant advancements in brain-computer interfaces (BCIs) can lead to the development
of enhanced decision-making platforms. Irrational behavior generating potential negative …
of enhanced decision-making platforms. Irrational behavior generating potential negative …
EEG-based emotion classification in financial trading using deep learning: Effects of risk control measures
B Tripathi, RK Sharma - Sensors, 2023 - mdpi.com
Day traders in the financial markets are under constant pressure to make rapid decisions
and limit capital losses in response to fluctuating market prices. As such, their emotional …
and limit capital losses in response to fluctuating market prices. As such, their emotional …
Design and Development of a Non-Contact ECG-Based Human Emotion Recognition System Using SVM and RF Classifiers
Emotion recognition becomes an important aspect in the development of human-machine
interaction (HMI) systems. Positive emotions impact our lives positively, whereas negative …
interaction (HMI) systems. Positive emotions impact our lives positively, whereas negative …
An investigation of the multi-dimensional (1D vs. 2D vs. 3D) analyses of EEG signals using traditional methods and deep learning-based methods
Electroencephalographic (EEG) signals are electrical signals generated in the brain due to
cognitive activities. They are non-invasive and are widely used to assess neurodegenerative …
cognitive activities. They are non-invasive and are widely used to assess neurodegenerative …
Multi-classifier fusion based on MI–SFFS for cross-subject emotion recognition
H Yang, S Huang, S Guo, G Sun - Entropy, 2022 - mdpi.com
With the widespread use of emotion recognition, cross-subject emotion recognition based
on EEG signals has become a hot topic in affective computing. Electroencephalography …
on EEG signals has become a hot topic in affective computing. Electroencephalography …
Emotion recognition by correlating facial expressions and EEG analysis
Emotion recognition is a fundamental task that any affective computing system must perform
to adapt to the user's current mood. The analysis of electroencephalography signals has …
to adapt to the user's current mood. The analysis of electroencephalography signals has …
An enhanced Coati Optimization Algorithm for global optimization and feature selection in EEG emotion recognition
EH Houssein, A Hammad, MM Emam, AA Ali - Computers in Biology and …, 2024 - Elsevier
Emotion recognition based on Electroencephalography (EEG) signals has garnered
significant attention across diverse domains including healthcare, education, information …
significant attention across diverse domains including healthcare, education, information …