Emotion recognition plays a crucial role in human-computer interaction, and electroencephalography (E...
Codegithub.com/yi-ding-cs/TSception 简介:脑电数可以视为二维时间序列,其维度分别是通道(脑电电极)和时间。时间维度反映了大脑活动随时间的变化。空间维度可以显示由于大脑上电极的不同位置而导致的不同功能区域的大脑激活模式。脑电信号在不同频段包含丰富的信息。 TSception 被提出来识别与用户情绪状态相对应...
Emotion recognition plays a vital role in Brain-Computer Interaction. To extract and employ the inherent information implied by functional connections among EEG electrodes, we propose a multichannel EEG emotion recognition method using convolutional neural network (CNN) with functional connectivity as input...
Domain adaptation methods using electroencephalography (EEG) play an important role in cross-subject emotion recognition. However, enhancing the generalizability of such models remains challenging. This paper proposes a domain adversarial neural network using multiple adversarial tasks (DANN-MAT). Multiple...
Code and data for "Real-time EEG-based Emotion Recognition Model using Principal Component Analysis and Tree-based Models for Neurohumanities" (Frontiers in Human Neuroscience, 2024) - miltoncandela/neurohumanities-lab
To address the problems of insufficient dimensionality of electroencephalogram (EEG) feature extraction, the tendency to ignore the importance of different sequential data segments, and the poor generalization ability of the model in EEG based emotion recognition, the model of convolutional neural network...
Code: GitHub - kanhaoning/Self-supervised-group-meiosis-contrastive-learning-for-EEG-based-emotion-recognitiongithub.com/kanhaoning/Self-supervised-group-meiosis-contrastive-learning-for-EEG-based-emotion-recognition 1、Movitation 一般来说,人工标签对于训练基于常见监督方法的深度学习模型至关重要。但有...
Emotion recognition using electroencephalography (EEG) signals has garnered widespread attention in recent years. However, existing studies have struggled to develop a sufficiently generalized model suitable for different datasets without re-training (cross-corpus). This difficulty arises because distribution...
Emotion recognition plays a vital role in Brain-Computer Interaction. To extract and employ the inherent information implied by functional connections among EEG electrodes, we propose a multichannel EEG emotion recognition method using convolutional neural network (CNN) with functional connectivity as input...
Multimodal emotion recognition from physiological signals is receiving an increasing amount of attention due to the impossibility to control them at will unlike behavioral reactions, thus providing more reliable information. Existing deep learning-based methods still rely on extracted handcrafted features, ...