[HTML][HTML] Subject independent emotion recognition from EEG using VMD and deep learning

P Pandey, KR Seeja - Journal of King Saud University-Computer and …, 2022 - Elsevier
Emotion recognition from Electroencephalography (EEG) is proved to be a good choice as it
cannot be mimicked like speech signals or facial expressions. EEG signals of emotions are …

EEG emotion recognition based on the attention mechanism and pre-trained convolution capsule network

S Liu, Z Wang, Y An, J Zhao, Y Zhao… - Knowledge-Based Systems, 2023 - Elsevier
Given the rapid development of brain–computer interfaces, emotion identification based on
EEG signals has emerged as a new study area with tremendous importance in recent years …

Recognition of Emotions Using Multichannel EEG Data and DBN‐GC‐Based Ensemble Deep Learning Framework

H Chao, H Zhi, L Dong, Y Liu - Computational intelligence and …, 2018 - Wiley Online Library
Fusing multichannel neurophysiological signals to recognize human emotion states
becomes increasingly attractive. The conventional methods ignore the complementarity …

Investigating the use of pretrained convolutional neural network on cross-subject and cross-dataset EEG emotion recognition

Y Cimtay, E Ekmekcioglu - Sensors, 2020 - mdpi.com
The electroencephalogram (EEG) has great attraction in emotion recognition studies due to
its resistance to deceptive actions of humans. This is one of the most significant advantages …

EEG-based emotion recognition using logistic regression with Gaussian kernel and Laplacian prior and investigation of critical frequency bands

C Pan, C Shi, H Mu, J Li, X Gao - Applied sciences, 2020 - mdpi.com
Emotion plays a nuclear part in human attention, decision-making, and communication.
Electroencephalogram (EEG)-based emotion recognition has developed a lot due to the …

Subject independent emotion recognition using EEG signals employing attention driven neural networks

AS Rajpoot, MR Panicker - Biomedical Signal Processing and Control, 2022 - Elsevier
Electroencephalogram (EEG) based emotional analysis has been employed in medical
science, security and human–computer interaction with good success. In the recent past …

Emotion recognition with machine learning using EEG signals

O Bazgir, Z Mohammadi… - 2018 25th national and …, 2018 - ieeexplore.ieee.org
In this research, an emotion recognition system is developed based on valence/arousal
model using electroencephalography (EEG) signals. EEG signals are decomposed into the …

Emotion recognition from EEG signal using XGBoost algorithm

S Parui, AKR Bajiya, D Samanta… - 2019 IEEE 16th India …, 2019 - ieeexplore.ieee.org
Of late, emotion detection from brain signal has become a topic of research. Various
machine learning algorithms have been applied to classify the emotion as a psychological …

Automated emotion recognition based on higher order statistics and deep learning algorithm

R Sharma, RB Pachori, P Sircar - Biomedical Signal Processing and …, 2020 - Elsevier
The objective of this paper is online recognition of human emotions based on
electroencephalogram (EEG) signals. The emotions are originated from the central and …

[PDF][PDF] Emotion recognition based on EEG using LSTM recurrent neural network

S Alhagry, AA Fahmy… - International Journal of …, 2017 - pdfs.semanticscholar.org
Emotion is the most important component in daily interaction between people. Nowadays, it
is important to make the computers understand user's emotion who interacts with it in human …