EEG emotion recognition using fusion model of graph convolutional neural networks and LSTM
In recent years, graph convolutional neural networks have become research focus and
inspired new ideas for emotion recognition based on EEG. Deep learning has been widely …
inspired new ideas for emotion recognition based on EEG. Deep learning has been widely …
Automated feature extraction on AsMap for emotion classification using EEG
Emotion recognition using EEG has been widely studied to address the challenges
associated with affective computing. Using manual feature extraction methods on EEG …
associated with affective computing. Using manual feature extraction methods on EEG …
Interpretable emotion recognition using EEG signals
Electroencephalogram (EEG) signal-based emotion recognition has attracted wide interests
in recent years and has been broadly adopted in medical, affective computing, and other …
in recent years and has been broadly adopted in medical, affective computing, and other …
Continuous convolutional neural network with 3D input for EEG-based emotion recognition
Y Yang, Q Wu, Y Fu, X Chen - … 2018, Siem Reap, Cambodia, December 13 …, 2018 - Springer
Automatic emotion recognition based on EEG is an important issue in Brain-Computer
Interface (BCI) applications. In this paper, baseline signals were taken into account to …
Interface (BCI) applications. In this paper, baseline signals were taken into account to …
Multi-domain feature fusion for emotion classification using DEAP dataset
Emotion recognition in real-time using electroencephalography (EEG) signals play a key
role in human-computer interaction and affective computing. The existing emotion …
role in human-computer interaction and affective computing. The existing emotion …
[HTML][HTML] EEG-based emotion recognition: Review of commercial EEG devices and machine learning techniques
Emotion recognition based on electroencephalography (EEG) signal features is now one of
the booming big data research areas. As the number of commercial EEG devices in the …
the booming big data research areas. As the number of commercial EEG devices in the …
Emotion recognition with convolutional neural network and EEG-based EFDMs
Electroencephalogram (EEG), as a direct response to brain activity, can be used to detect
mental states and physical conditions. Among various EEG-based emotion recognition …
mental states and physical conditions. Among various EEG-based emotion recognition …
[HTML][HTML] Employing PCA and t-statistical approach for feature extraction and classification of emotion from multichannel EEG signal
To achieve a highly efficient brain-computer interface (BCI) system regarding emotion
recognition from electroencephalogram (EEG) signal, the most crucial issues are feature …
recognition from electroencephalogram (EEG) signal, the most crucial issues are feature …
Emotion recognition from multi-channel EEG via deep forest
Recently, deep neural networks (DNNs) have been applied to emotion recognition tasks
based on electroencephalography (EEG), and have achieved better performance than …
based on electroencephalography (EEG), and have achieved better performance than …
[HTML][HTML] IDEA: Intellect database for emotion analysis using EEG signal
VM Joshi, RB Ghongade - Journal of King Saud University-Computer and …, 2022 - Elsevier
Emotion recognition using Electroencephalography (EEG) is a convenient and reliable
technique. EEG based emotion detection study can find its application in various fields such …
technique. EEG based emotion detection study can find its application in various fields such …