A comprehensive review of dimensionality reduction techniques for feature selection and feature extraction
Due to sharp increases in data dimensions, working on every data mining or machine
learning (ML) task requires more efficient techniques to get the desired results. Therefore, in …
learning (ML) task requires more efficient techniques to get the desired results. Therefore, in …
Current status, challenges, and possible solutions of EEG-based brain-computer interface: a comprehensive review
Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices
through the utilization of brain waves. It is worth noting that the application of BCI is not …
through the utilization of brain waves. It is worth noting that the application of BCI is not …
Emotion recognition from EEG signal focusing on deep learning and shallow learning techniques
Recently, electroencephalogram-based emotion recognition has become crucial in enabling
the Human-Computer Interaction (HCI) system to become more intelligent. Due to the …
the Human-Computer Interaction (HCI) system to become more intelligent. Due to the …
Review on emotion recognition based on electroencephalography
H Liu, Y Zhang, Y Li, X Kong - Frontiers in Computational …, 2021 - frontiersin.org
Emotions are closely related to human behavior, family, and society. Changes in emotions
can cause differences in electroencephalography (EEG) signals, which show different …
can cause differences in electroencephalography (EEG) signals, which show different …
Emotion detection using electroencephalography signals and a zero-time windowing-based epoch estimation and relevant electrode identification
Recognizing emotions using biological brain signals requires accurate and efficient signal
processing and feature extraction methods. Existing methods use several techniques to …
processing and feature extraction methods. Existing methods use several techniques to …
EEG emotion recognition using improved graph neural network with channel selection
X Lin, J Chen, W Ma, W Tang, Y Wang - Computer Methods and Programs …, 2023 - Elsevier
Background and objective: Emotion classification tasks based on electroencephalography
(EEG) are an essential part of artificial intelligence, with promising applications in healthcare …
(EEG) are an essential part of artificial intelligence, with promising applications in healthcare …
[HTML][HTML] Review of the emotional feature extraction and classification using EEG signals
J Wang, M Wang - Cognitive robotics, 2021 - Elsevier
As a subjectively psychological and physiological response to external stimuli, emotion is
ubiquitous in our daily life. With the continuous development of the artificial intelligence and …
ubiquitous in our daily life. With the continuous development of the artificial intelligence and …
Can emotion be transferred?—A review on transfer learning for EEG-based emotion recognition
W Li, W Huan, B Hou, Y Tian, Z Zhang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The issue of electroencephalogram (EEG)-based emotion recognition has great academic
and practical significance. Currently, there are numerous research trying to address this …
and practical significance. Currently, there are numerous research trying to address this …
A multilayer stacking method base on RFE-SHAP feature selection strategy for recognition of driver's mental load and emotional state
J Huang, Y Peng, L Hu - Expert Systems with Applications, 2024 - Elsevier
The driver state monitoring is becoming one of the research hotspots in the field of traffic and
vehicle safety, which can ensure driving safety by monitoring the driver's state. Therefore …
vehicle safety, which can ensure driving safety by monitoring the driver's state. Therefore …
EEG emotion recognition based on TQWT-features and hybrid convolutional recurrent neural network
M Zhong, Q Yang, Y Liu, B Zhen, B Xie - Biomedical signal processing …, 2023 - Elsevier
Electroencephalogram (EEG)-based emotion recognition has gained high attention in Brain-
Computer Interfaces. However, due to the non-linearity and non-stationarity of EEG signals …
Computer Interfaces. However, due to the non-linearity and non-stationarity of EEG signals …