Emotions recognitionDatasetVirtual realityVirtual environmentVirtual reality EEG (VREEG)Frequency bandsEmotion recognition is essential in human interaction and understanding, significantly impacting cognition, perception, learning, communication, and decision-making. The classification of emotions from EEG signals...
methods. The Emotion in EEG-Audio-Visual (EAV) dataset represents the first public dataset to incorporate three primary modalities for emotion recognition within a conversational context. We anticipate that this dataset will make significant contributions to the modeling of the human emotional process, ...
SEED is a publicly available EEG emotion recognition dataset collected by researchers at Shanghai Jiao Tong University (Zheng & Lu, 2015). It includes data from 15 participants (7 males and 8 females). The researchers chose 15 movie clips as stimuli, each lasting approximately 4 min and contai...
通过对这些数据的分析,研究人员能够更全面地理解人类情感的表现形式,为开发更先进的情感识别模型提供了宝贵的资源。他们的技术论文《EaV: EEG-audio-Video Dataset for Emotion Recognition in Conversational Contexts》发表于自然(Nature)Scientific Data子刊。 EaV数据集的开发由纳扎尔巴耶夫大学计算机科学系和高丽大学人工...
checkpoints, and high-quality labels of the CVA-BUS dataset used in our experiments.【6】强化半...
EEG Alpha Waves Dataset; Centre pour la Communication Scientifique Directe: Grenoble, France, 2019. 29. Katsigiannis, S.; Ramzan, N. DREAMER: A database for emotion recognition through EEG and ECG signals from wireless low-cost off-the-shelf devices. IEEE J. Biomed. Heal. Informatics 2...
dataset (Jenke et al. 2014). For classifying the extracted emotion features, many researchers have adopted machine learning methods over the past few years (Kim et al. 2013). Li et al. apply a linear support vector machine (SVM) to classify emotion features extracted from the gamma ...
EEG-Emotion-Recognition Ne**er上传209.95 MB文件格式zipbicepstrumbicoherencebispectrumcepstral-analysisdeap-dataseteeg-signalsseed-database EEG-Emotion-Recognition是一种通过脑电图(EEG)信号来识别情绪的方法。该方法基于高阶统计学(HOS)技术,通过分析EEG信号中的非线性、非高斯特征来推断个体的情绪状态。
We introduce a multimodal emotion dataset comprising data from 30-channel electroencephalography (EEG), audio, and video recordings from 42 participants. Each participant engaged in a cue-based conversation scenario, eliciting five distinct emotions: neutral(N), anger(A), happiness(H), sadness(S...
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 used in emotion recognition, but it is still challenging to construct models and algorithms in practical applications. In this ...