Emotion recognition in EEG signals using deep learning methods: A review
Emotions are a critical aspect of daily life and serve a crucial role in human decision-making,
planning, reasoning, and other mental states. As a result, they are considered a significant …
planning, reasoning, and other mental states. As a result, they are considered a significant …
A review of AI cloud and edge sensors, methods, and applications for the recognition of emotional, affective and physiological states
Affective, emotional, and physiological states (AFFECT) detection and recognition by
capturing human signals is a fast-growing area, which has been applied across numerous …
capturing human signals is a fast-growing area, which has been applied across numerous …
An investigation of olfactory-enhanced video on EEG-based emotion recognition
M Wu, W Teng, C Fan, S Pei, P Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Collecting emotional physiological signals is significant in building affective Human-
Computer Interactions (HCI). However, how to evoke subjects' emotions efficiently in EEG …
Computer Interactions (HCI). However, how to evoke subjects' emotions efficiently in EEG …
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 …
Design of subject independent 3D VAD emotion detection system using EEG signals and machine learning algorithms
This work aims to develop a subject-independent Emotion Detection System (EDS) based
on EEG signals and the 3D Valence-Arousal-Dominance (VAD) model. The DEAP database …
on EEG signals and the 3D Valence-Arousal-Dominance (VAD) model. The DEAP database …
Cross-subject EEG emotion recognition using multi-source domain manifold feature selection
Recent researches on emotion recognition suggests that domain adaptation, a form of
transfer learning, has the capability to solve the cross-subject problem in Affective brain …
transfer learning, has the capability to solve the cross-subject problem in Affective brain …
Evaluating ensemble learning methods for multi-modal emotion recognition using sensor data fusion
Automatic recognition of human emotions is not a trivial process. There are many factors
affecting emotions internally and externally. Expressing emotions could also be performed in …
affecting emotions internally and externally. Expressing emotions could also be performed in …
A review of multimodal emotion recognition from datasets, preprocessing, features, and fusion methods
B Pan, K Hirota, Z Jia, Y Dai - Neurocomputing, 2023 - Elsevier
Affective computing is one of the most important research fields in modern human–computer
interaction (HCI). The goal of affective computing is to study and develop the theories …
interaction (HCI). The goal of affective computing is to study and develop the theories …
A new fuzzy-based classification method for use in smart/precision medicine
E Zaitseva, V Levashenko, J Rabcan, M Kvassay - Bioengineering, 2023 - mdpi.com
The development of information technology has had a significant impact on various areas of
human activity, including medicine. It has led to the emergence of the phenomenon of …
human activity, including medicine. It has led to the emergence of the phenomenon of …
Henry gas solubility optimization with deep learning based facial emotion recognition for human computer Interface
Automated facial emotion recognition (FER) is one of the important fields of human-
computer interaction (HCI). FER remains challenging due to facial accessories, non-uniform …
computer interaction (HCI). FER remains challenging due to facial accessories, non-uniform …