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研究方向相关工作整理

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本篇博客整理一些个人研究领域相关的重要文献。

研究方向

EEG情绪识别

年份标题作者期刊/会议模态创新/方法类别结果开源解读
2018EEG Emotion Recognition Using Dynamical Graph Convolutional Neural NetworksAIPLTAFFCEEG动态图卷积神经网络（DGCNN）图神经网络SEED
DREAMER		Github知乎
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2020EEG-based emotion recognition using simple recurrent units network and ensemble learningSMECPBSPCEEG深度简单循环单元网络（SRU）循环神经网络自采Github学者网
2022Deep continual learning for emerging emotion recognition
2021Contrastive learning of subject-invariant EEG representations for cross-subject emotion recognition公众号
知乎
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2022EEG-based emotion recognition via efficient convolutional neural network and contrastive learning
2021EEG Based Emotion Recognition by Combining Functional Connectivity Network and Local Activations学者网
2022Uncovering the Structure of Clinical EEG Signals with Self-Supervised Learning
2020Contrastive Representation Learning for Electroencephalogram Classification
2004Intersubject Synchronization of Cortical Activity During Natural Vision
2020Correlated Components of Ongoing EEG Point to Emotionally Laden Attention – a Possible Marker of Engagement?
2016Domain-Adversarial Training of Neural Networks
2022Reducing the Subject Variability of EEG Signals with Adversarial Domain Generalization
2011Domain Adaptation Via Transfer Component Analysis
2018A BiHemisphere Domain Adversarial Neural Network Model for EEG Emotion Recognition
2019Domain Adaptation for EEG Emotion Recognition Based on Latent Representation Similarity
2019Reducing the Subject Variability of EEG Signals with Adversarial Domain Generalization
2021Plug-and-Play Domain Adaptation for Cross-Subject EEG-Based Emotion Recognition学者网
2014EEG-based emotion recognition using deep learning network with principal component based covariate shift adaptation
2019Individual similarity guided transfer modeling for EEG-based emotion recognition
2020Transfer components between subjects for EEG-based emotion recognition
2017Improving EEG-based emotion classification using conditional transfer learning
2020Domain adaptation techniques for EEG-based emotion recognition: A comparative study on two public datasets
2019Constructing a personalized cross-day EEG-based emotionclassification model using transfer learning
2016Unsupervised domain adaptation techniques based on auto-encoder for non-stationary EEG-based emotion recognition
2020EEG-based emotion recognition using domain adaptation network
2018WGAN domain adaptation for EEG-based emotion recognition
2021Multisource transfer learning for cross-subject EEG emotion recognition
2016Personalizing EEG-based affective models with transfer learning
2018Hierarchical convolutional neural networks for EEG-based emotion recognition
2021HetEmotionNet: Two-Stream Heterogeneous Graph Recurrent Neural Network for Multi-modal Emotion Recognition学者网
2021Classification of Complex Emotions Using EEG and Virtual Environment: Proof of Concept and Therapeutic Implication学者网
2021BENDR: Using Transformers and an Contrastive Self-Supervised Learning Task to Learn fromMassive Amount of EEG Data学者网
2020Leveraging spatial-temporal convolutional features for EEG-based emotion recognition学者网
2021Influence of music liking on EEG based emotion recognition学者网
2020Data Augmentation for Enhancing EEG-based Emotion Recognition with Deep Generative Models学者网
2021基于多源域自适应的跨被试情感脑电识别学者网
2022GANSER: A Self-supervised Data Augmentation Framework for EEG-based Emotion Recognition学者网
2022Cross-subject EEG emotion recognition combined with connectivity features and meta-transfer learning学者网
2023Cross-disciplinary emotion recognition based on similarity of EEG signal transfer learning domain学者网
2021Investigating of Deaf Emotion Cognition Pattern By EEG and Facial Expression Combination学者网
2023Efficient neural architecture search for emotion recognition学者网
2023BIOT: Cross-data Biosignal Learning in the Wild学者网
2022The Effect of Music Listening on EEG Functional Connectivity of Brain: A Short-Duration and Long-Duration Study学者网
2021Cross-subject EEG emotion classification based on few-label adversarial domain adaption学者网
2024HiCMAE: Hierarchical Contrastive Masked Autoencoder for self-supervised Audio-Visual Emotion Recognition学者网
2024Identifying the Hierarchical Emotional Areas in the Human Brain Through Information Fusion学者网
2024SFT-SGAT: A semi-supervised fine-tuning self-supervised graph attention network for emotion recognition and consciousness detection学者网
2024Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI学者网
2024EEGPT: Unleashing the Potential of EEG Generalist Foundation Model by Autoregressive Pre-training学者网
2024EEGPT: Pretrained Transformer for Universal and Reliable Representation of EEG Signals学者网
2024Brant-X: A Unified Physiological Signal Alignment Framework学者网
2024Cross-Modal Guiding Neural Network for Multimodal Emotion Recognition From EEG and Eye Movement Signals学者网
2024Grop: Graph Orthogonal Purification Network for EEG Emotion Recognition学者网
2024Hybrid Network Using Dynamic Graph Convolution and Temporal Self-Attention for EEG-Based Emotion Recognition学者网
2024Light-weight residual convolution-based capsule network for EEG emotion recognition学者网
2024Multi-view domain-adaptive representation learning for EEG-based emotion recognition学者网
2023Learning Topology-Agnostic EEG Representations with Geometry-Aware Modeling学者网
2025BrainUICL: An Unsupervised Individual Continual Learning Framework for EEG Applications学者网
2023EEGMatch: Learning with Incomplete Labels for Semi-Supervised EEG-based Cross-Subject Emotion Recognition学者网
2025AnchorInv: Few-Shot Class-Incremental Learning of Physiological Signals via Feature Space-Guided Inversion学者网
2024Language-Guided Transformer for Federated Multi-Label Classification学者网
2025SEEG Emotion Recognition Based on Transformer Network With Channel Selection and Explainability学者网
2025Multi-to-Single: Reducing Multimodal Dependency in Emotion Recognition Through Contrastive LearningSJTUAAAI 2025学者网
2022GMSS Graph-Based Multi-Task Self-Supervised Learning for EEG Emotion RecognitionCSDN
2023脑电情绪识别的深度学习研究综述软件学报
2022Using Facial Micro-Expressions in Combination With EEG and Physiological Signals for Emotion Recognition-
2023ST-SCGNN: A Spatio-Temporal Self-Constructing Graph Neural Network for Cross-Subject EEG-Based Emotion Recognition and Consciousness Detection
2025Cross-dataset EEG emotion recognition based on pre-trained Vision Transformer considering emotional sensitivity diversity
2024Enhanced Cross-Dataset Electroencephalogram-Based Emotion Recognition Using Unsupervised Domain Adaptation
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意识障碍辅助检测

年份标题作者期刊/会议数据集被试方法结果开源

Hybrid Asynchronous Brain-Computer Interface for Yes/No Communication in Patients with Disorders of Consciousness
用于意识障碍患者是/否通信的混合异步脑机接口
https://www.scholat.com/teamwork/showPostMessage.html?id=12131

How brain-computer interface technology may improve the diagnosis of the disorders of consciousness: A comparative study
脑机接口技术如何改善意识障碍的诊断：一项比较研究
https://www.scholat.com/teamwork/showPostMessage.html?id=12257

A simple intervention for disorders of consciousness- is there a light at the end of the tunnel?
针对意识障碍的简易干预措施——是否已现曙光？
https://www.scholat.com/teamwork/showPostMessage.html?id=13033

Standardized visual EEG features predict outcome in patients with acute consciousness impairment of various etiologies
标准化视觉脑电特征可预测不同病因急性意识障碍患者的预后
https://www.scholat.com/teamwork/showPostMessage.html?id=13039

EEG complexity correlates with residual consciousness level of disorders of consciousness
脑电图复杂度与意识障碍中残留意识水平相关
https://www.scholat.com/teamwork/showPostMessage.html?id=13204

Brain-Computer Interfaces in Disorders of Consciousness
意识障碍中的脑机接口
https://mp.weixin.qq.com/s?__biz=MzAxNjIxNzM1Nw==&mid=2454468717&idx=1&sn=07559c3544b28b63b5e330cce816c6cf

Accuracy of EEG Biomarkers in the Detection of Clinical Outcome in Disorders of Consciousness after Severe Acquired Brain Injury: Preliminary Results of a Pilot Study Using a Machine Learning Approach
严重获得性脑损伤后意识障碍临床结局检测中脑电生物标志物的准确性：基于机器学习方法的初步研究结果
https://www.scholat.com/teamwork/showPostMessage.html?id=13539

tDCS-EEG for Predicting Outcome in Patients With Unresponsive Wakefulness Syndrome
tDCS-EEG用于无清醒反应综合征患者的预后预测
https://www.scholat.com/teamwork/showPostMessage.html?id=14962

DOCTer: a novel EEG-based diagnosis framework for disorders of consciousness
DOCTer: 一种基于EEG的新型意识障碍诊断框架
https://www.scholat.com/teamwork/showPostMessage.html?id=16217

Uncovering Brain Network Insights for Prognosis in Disorders of Consciousness: EEG Source Space Analysis and Brain Dynamics
探索意识障碍预后的大脑网络：脑电图源空间分析与脑动力学
https://www.scholat.com/teamwork/showPostMessage.html?id=16248

Decoding Musical Neural Activity in Patients with Disorders of Consciousness through Self-Supervised Contrastive Domain Generalization
自监督对比域泛化技术解码意识障碍患者的音乐神经活动
https://www.scholat.com/teamwork/showPostMessage.html?id=16292

A Hybrid BCI Integrating EEG and Eye-tracking for Assisting Clinical Communication in Patients with Disorders of Consciousness
一种整合脑电图与眼动追踪技术的混合式脑机接口，用于辅助意识障碍患者的临床沟通
https://www.scholat.com/teamwork/showPostMessage.html?id=16312

SFT-SGAT: A semi-supervised fine-tuning self-supervised graph attention network for emotion recognition and consciousness detection
SFT-SGAT：一种用于情绪识别和意识检测的半监督微调自监督图注意力网络
https://www.scholat.com/teamwork/showPostMessage.html?id=16390

A Theoretically Based Index of Consciousness Independent of Sensory Processing and Behavior
一种不依赖于感知行为的意识评估指数
https://www.scholat.com/teamwork/showPostMessage.html?id=16842

The Characteristics of Electroencephalogram Signatures in Minimally Conscious State Patients Induced by General Anesthesia
全麻诱导的最低意识状态患者的脑电图特征
c133aeb9.html

Look into my eyes: What can eye-based measures tell us about the relationship between physical activity and cognitive performance?
凝视我的双眼：基于眼动的研究能为我们揭示身体活动与认知表现之间的关系吗？
8815f4d9.html

Quantifying arousal and awareness in altered states of consciousness using interpretable deep learning
利用可解释深度学习量化改变意识状态中的唤醒度与觉知度
6dbf11cc.html

Detecting Disorders of Consciousness in Brain Injuries From EEG Connectivity Through Machine Learning
基于脑电连接性与机器学习检测脑损伤中的意识障碍
e6592f93.html

Assessing the depth of language processing in patients with disorders of consciousness
评估意识障碍患者的语言处理深度
a5b3ddd1.html

An EEG-Based Brain Computer Interface for Emotion Recognition and Its Application in Patients with Disorder of Consciousness
基于脑电图的情绪识别脑机接口及其在意识障碍患者中的应用

ST-SCGNN: A Spatio-Temporal Self-Constructing Graph Neural Network for Cross-Subject EEG-Based Emotion Recognition and Consciousness Detection
ST-SCGNN：面向跨被试EEG情感识别与意识检测的时空自构图神经网络