EEG|Based Emotion Recognition Using Spatial|Temporal Connectivity

EEG-Based Emotion Recognition Using Spatial-Temporal Connectivity

By quantifying the connectivity strength of EEG signal channels within and across time intervals, spatial-temporal connectivity features are ...

EEG-Based Emotion Recognition Using Spatial-Temporal ...

... recognition via a proposed model, spatial-temporal-connective muti-scale convolutional neural network (STC-CNN). The channel-to-channel ...

EEG-Based Emotion Recognition Using Spatial-Temporal Connectivity

Emotion Recognition using Multimodal Residual LSTM Network ... Various studies have shown that the temporal information captured by conventional long-short-term ...

EEG-Based Emotion Recognition Using Spatial-Temporal Graph ...

We design a hybrid model called ST-GCLSTM, which comprises a spatial-graph convolutional network (SGCN) module and an attention-enhanced bi-directional Long ...

(PDF) EEG-Based Emotion Recognition Using Spatial-Temporal ...

The channel-to-channel connectivity is gotten to describe brain region-to-region cooperation under emotion stimuli. The STC-CNN achieved an average accuracy of ...

Emotion recognition using spatial-temporal EEG features through ...

In this paper, we present a spatial-temporal feature fused convolutional graph attention network (STFCGAT) model based on multi-channel EEG signals for human ...

EEG-based emotion recognition using a temporal-difference ...

In this paper, based on prior knowledge that emotion varies slowly across time, we propose a temporal-difference minimizing neural network (TDMNN) for EEG ...

Leveraging spatial-temporal convolutional features for EEG-based ...

(2) The dimension of valence also obtains comparable emotion recognition performance with the accuracy of 87.84%, which surpass the most of the state-of-the-art ...

Emotion recognition using hierarchical spatial-temporal learning ...

This paper designs a transformer-based method, denoted by R2G-STLT, which relies on a spatial–temporal transformer encoder with regional to global hierarchical ...

Adaptive Spatial–Temporal Aware Graph Learning for EEG-Based ...

From regional to global brain: A novel hierarchical spatial-temporal neural network model for EEG emotion recognition. ... EEG-based emotion recognition using ...

Improved EEG-based emotion recognition through information ...

Convolutional neural network approach for EEG-based emotion recognition using brain connectivity and its spatial information. In 2018 IEEE ...

Electroencephalograph-Based Emotion Recognition Using Brain ...

These connectivity feature representations not only contain the inherent timing and spatial information of the original EEG data but also ...

Multi-scale spatiotemporal representation learning for EEG-based ...

... network for EEG emotion recognition. The network comprises two ... Zhang, “Eeg-based emotion recognition using spatial-temporal graph ...

STGATE: Spatial-temporal graph attention network with a ... - Frontiers

This neural activity can be directly measured using EEG devices, making EEG-based emotion recognition increasingly popular in various fields, such as education, ...

Temporal shift residual network for EEG-based emotion recognition

We convert EEG data into feature image sequences with 3D representation, which fully preserve the spatial, spectral and temporal structure of ...

EEG-Based Emotion Recognition Using Temporal Convolutional ...

A sequence model based on deep-learning that uses Temporal Convolutional Network (TCN) to extract high-level features in consideration of the time ...

Spatial–temporal features-based EEG emotion recognition using ...

Spatial–temporal features-based EEG emotion recognition using graph convolution network and long short-term memory, Fa Zheng, Bin Hu, Xiangwei Zheng, ...

ASTDF-Net: Attention-Based Spatial-Temporal Dual-Stream Fusion ...

Emotion recognition based on eeg using lstm recurrent neural network. International Journal of Advanced Computer Science and Applications ...

FBSTCNet: A Spatio-Temporal Convolutional Network Integrating ...

Electroencephalography (EEG)-based emotion recognition plays a key role in the development of affective brain-computer interfaces (BCIs).

Spatio-Temporal Representation of an Electoencephalogram for ...

Deep neural network (DNN) approaches using an EEG for emotion recognition have recently shown remarkable improvement in terms of their recognition accuracy.