脑机接口 / BCI

Towards Automated EEG-Based Epilepsy Detection Using Deep Convolutional Autoencoders

基于深度卷积自编码器的自动脑电图癫痫检测方法

Annika Stiehl, Nicolas Weeger, Christian Uhl, Dominic Bechtold, Nicole Ille, Stefan Geißelsöder

专题命中 EEG解码 ：EEG(title,abstract)；分类 eess.SP

AI总结 本文提出基于深度卷积自编码器的自动脑电图癫痫检测方法，通过结合时间和频率损失提升EEG信号重建性能，验证了深度学习在处理EEG数据时对频域信息的捕捉能力。

Comments \c{opyright} 2025 IEEE in 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2025

GAPses: Versatile smart glasses for comfortable and fully-dry acquisition and parallel ultra-low-power processing of EEG and EOG

GAPses: 用于舒适且完全干燥获取和并行超低功耗处理EEG和EOG的多功能智能眼镜

Sebastian Frey, Mattia Alberto Lucchini, Victor Kartsch, Thorir Mar Ingolfsson, Andrea Helga Bernardi, Michael Segessenmann, Jakub Osieleniec, Simone Benatti, Luca Benini, Andrea Cossettini

专题命中 EEG解码 ：EEG(title,abstract)；分类 eess.SP

AI总结 GAPses是一种多功能智能眼镜，用于舒适且完全干燥获取并行超低功耗处理EEG和EOG信号，实现高精度生物识别和眼动分类。

Comments 11 pages, 6 figures

QuanvNeXt: An end-to-end quanvolutional neural network for EEG-based detection of major depressive disorder

QuanvNeXt：一种用于基于EEG的抑郁症检测的端到端量化卷积神经网络

Nabil Anan Orka, Ehtashamul Haque, Maftahul Jannat, Md Abdul Awal, Mohammad Ali Moni

机构 * The University of Queensland（昆士兰大学） ； BRAC University（布拉克大学） ； Bangladesh Medical University（孟加拉医学大学） ； University of Southern Queensland（南方昆士兰大学） ； Charles Sturt University（查尔斯·斯特劳特大学） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

AI总结 QuanvNeXt通过引入新颖的交叉残差块，实现了高效且可靠的EEG抑郁症检测，准确率高达93.1%

Comments Under review

Convolutional Monge Mapping between EEG Datasets to Support Independent Component Labeling

卷积蒙日映射在EEG数据集之间进行转换以支持独立成分标注

Austin Meek, Carlos H. Mendoza-Cardenas, Austin J. Brockmeier

机构 * Department of Computer and Information Sciences University of Delaware（计算机与信息科学系德克萨斯大学） ； Twitch Interactive Inc.（Twitch互动公司） ； Department of Electrical and Computer Engineering Department of Computer and Information Sciences University of Delaware（电气与计算机工程系计算机与信息科学系德克萨斯大学） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

AI总结 本文提出了一种改进的卷积蒙日映射方法，通过两种新方法实现EEG数据集之间的映射，以提高独立成分分类的准确性。

Comments Code available at: https://github.com/cniel-ud/ICWaves; Accepted to NeurIPS 2025 Workshop on Learning from Time Series for Health

xEEGNet: Towards Explainable AI in EEG Dementia Classification

xEEGNet：迈向EEG痴呆分类中的可解释人工智能

Andrea Zanola, Louis Fabrice Tshimanga, Federico Del Pup, Marco Baiesi, Manfredo Atzori

机构 * Department of Neuroscience, University of Padua（帕多瓦大学神经科学系） ； Padua Neuroscience Center（帕多瓦神经科学中心） ； Department of Information Engineering, University of Padua（帕多瓦大学信息工程系） ； Department of Physics and Astronomy, University of Padua（帕多瓦大学物理与天文学系） ； Information Systems Institute, University of Applied Sciences Western Switzerland (HES-SO Valais)（瑞士西部应用科学大学信息系统研究所） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

AI总结 xEEGNet通过减少参数和提升可解释性，在EEG痴呆分类中实现了高性能和低过拟合，展示了小型架构的有效性。

Journal ref J. Neural Eng. 22, 046042 (2025)

EEG Dynamic Microstate Patterns Induced by Pulsed Wave Transcranial Photobiomodulation Therapy

脉冲波颅内光生物调节疗法诱导的EEG动态微状态模式

Jiangshan He, Hui Xie, Yuqiang Yang, Chunli Jia, Dan Liang, Lianghua Zhang, Xiaoyu Wang, Tianyi Luo, Zexiao Dong, Huiting Yang, Zhen Yuan, Mingzhe Jiang, Xueli Chen

专题命中 EEG解码 ：EEG(title,abstract)；分类 q-bio.NC

AI总结 脉冲波tPBM疗法通过调节EEG微状态C模式，优化了脑功能网络参数，展示了其在神经调节中的应用潜力。

Comments 7 figures

Adapting Neural Audio Codecs to EEG

将神经音频编解码器适应于EEG

Ard Kastrati, Luca Lanzendörfer, Riccardo Rigoni, John Staib Matilla, Roger Wattenhofer

机构 * ETH Zurich（苏黎世联邦理工学院） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

AI总结 本文提出将预训练的神经音频编解码器适应于EEG压缩，通过多通道扩展和注意力机制提升EEG重建质量与泛化能力。

Comments Foundation Models for the Brain and Body (BrainBodyFM@NeurIPS)

Calibration-Free EEG-based Driver Drowsiness Detection with Online Test-Time Adaptation

无需校准的基于EEG的驾驶员困倦检测与在线测试时适应

Geun-Deok Jang, Dong-Kyun Han, Seo-Hyeon Park, Seong-Whan Lee

机构 * Department of Artificial Intelligence, Korea University（人工智能系，韩国大学） ； Department of Brain and Cognitive Engineering, Korea University（脑科学与认知工程系，韩国大学） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

AI总结 本文提出一种无需校准的EEG困倦检测方法，通过在线测试时适应技术提升模型对不同主体的适应能力，实验表明其在非独立同分布场景中性能优越。

Comments 10 pages, Submitted to IEEE Transactions on Human-Machine Systems

EEGAgent: A Unified Framework for Automated EEG Analysis Using Large Language Models

EEGAgent: 一种利用大语言模型进行自动化EEG分析的统一框架

Sha Zhao, Mingyi Peng, Haiteng Jiang, Tao Li, Shijian Li, Gang Pan

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

AI总结 EEGAgent利用大语言模型实现多任务EEG分析，提供灵活且可解释的自动化EEG处理与报告生成能力。

An Active Dry-Contact Continuous EEG Monitoring System for Seizure Detection Applications in Clinical Neurophysiology

一种用于临床神经生理学中癫痫检测的主动干接触连续EEG监测系统

Nima L. Wickramasinghe, Dinuka Sandun Udayantha, Akila Abeyratne, Kavindu Weerasinghe, Kithmin Wickremasinghe, Jithangi Wanigasinghe, Anjula De Silva, Chamira U. S. Edussooriya

专题命中 EEG解码 ：EEG(title,abstract)；分类 eess.SP

AI总结 本研究提出了一种低成本的主动干接触EEG头戴设备，结合深度学习模型和多模态伪影去除算法，用于实时检测婴儿癫痫发作。

Comments 10 pages, 9 figures, Work is accepted for publication in IEEE TBME

EVA-Net: Interpretable Anomaly Detection for Brain Health via Learning Continuous Aging Prototypes from One-Class EEG Cohorts

EVA-Net：通过从单类EEG群体学习连续衰老原型进行脑健康可解释性异常检测

Kunyu Zhang, Mingxuan Wang, Xiangjie Shi, Haoxing Xu, Chao Zhang

机构 * Qilu Hospital, ASU（青岛医院，亚利桑那州立大学） ； Zhengzhou University（郑州大学） ； University of Science and Technology Beijing（北京科技大学） ； Southern University of Science and Technology（南方科技大学） ； Qilu Hospital（青岛医院） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

AI总结 EVA-Net通过学习连续衰老原型，从单类EEG群体中实现脑健康可解释性异常检测，提升医疗数据处理的可解释性与准确性。

Artifacts Are Not Noise: Embodied Resonance and the 70% Signal Loss in Conventional EEG

Ahmed Gamal Eldin

专题命中 EEG解码 ：EEG(title,abstract)；分类 eess.SP

Comments v3: Major revision. Adds ICA vs. raw data comparison. Finds artifact rejection masks the core correlation (r=0.59 -> r=0.19), supporting an embodied cognition framework. R vs. ITC comparison added to main text. Expanded discussion on methodology, embodied resonance, & AI. Abstract & theory updated based on new data & feedback

A Quantitative Framework for Assessing Sleep Quality from EEG Time Series in Complex Dynamic Systems

Gi-Hwan Shin

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.HC

Comments Doctoral dissertation, Korea University, 2025

A simple EEG-based decision tool for neonatal therapeutic hypothermia in hypoxic-ischemic encephalopathy

Marc Fiammante, Anne-Isabelle Vermersch, Marie Vidailhet, Mario Chavez

专题命中 EEG解码 ：EEG(title,abstract)；分类 q-bio.NC

Comments 20 pages, 1 table, 2 figures

Emotional EEG Classification using Upscaled Connectivity Matrices

Chae-Won Lee, Jong-Seok Lee

机构 * School of Integrated Technology and the BK21 Graduate Program in Intelligent Semiconductor Technology（整合技术学院和智能半导体技术BK21研究生项目） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

Comments Accepted for SMC 2025

Incomplete Depression Feature Selection with Missing EEG Channels

Zhijian Gong, Wenjia Dong, Xueyuan Xu, Fulin Wei, Chunyu Liu, Li Zhuo

机构 * Beijing University of Technology, Beijing, China（北京理工大学） ； Anhui University, Hefei, China（安徽大学） ； North China Electric Power University, Beijing, China（华北电力大学） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

EMOD: A Unified EEG Emotion Representation Framework Leveraging V-A Guided Contrastive Learning

Yuning Chen, Sha Zhao, Shijian Li, Gang Pan

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

Adaptive EEG-based stroke diagnosis with a GRU-TCN classifier and deep Q-learning thresholding

Shakeel Abdulkareem, Bora Yimenicioglu, Khartik Uppalapati, Aneesh Gudipati, Adan Eftekhari, Saleh Yassin

机构 * George Mason University（乔治·马歇尔大学） ； Raregen Youth Network（Raregen青年网络） ； Translational Medical Research Department（转化医学研究部） ； Harvard University（哈佛大学） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

Comments 10 pages, 6 figures. Equal contribution: Shakeel Abdulkareem and Bora Yimenicioglu. Compiled with pdfLaTeX (wlscirep class)

One Model for All: Universal Pre-training for EEG based Emotion Recognition across Heterogeneous Datasets and Paradigms

Xiang Li, You Li, Yazhou Zhang

机构 * Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center inJinan), Qilu University of Technology (Shandong Academy of Sciences), Jinan, China and Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing, Shandong Fundamental Research Center for Computer Science, Jinan, China（教育部计算功率网络与信息安全重点实验室，山东计算机科学中心（济南国家超算中心），青岛科技大学（山东省科学院），济南，中国和山东省计算功率互联网与服务计算省级重点实验室，山东省计算机科学基础研究中心，济南，中国） ； College of Intelligence and Computing, Tianjin University（天津大学智能与计算学院） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

Towards Attention-Aware Large Language Models: Integrating Real-Time Eye-Tracking and EEG for Adaptive AI Responses

Dan Zhang

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.HC

Comments 9 pages

Variational Representational Similarity Analysis (vRSA) for M/EEG

Alex Lepauvre, Lucia Melloni, Karl Friston, Peter Zeidman

专题命中 EEG解码 ：EEG(title,abstract)；分类 q-bio.NC

Comments 24 pages, 7 figures, code available at https://github.com/pzeidman/vRSA_MEEG

FractalBrain: A Neuro-interactive Virtual Reality Experience using Electroencephalogram (EEG) for Mindfulness

Jamie Ngoc Dinh, You-Jin Kim, Myungin Lee

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.HC

Comments Extended Abstracts (Interactivity), 4 pages. Published at the 2024 CHI Conference on Human Factors in Computing Systems

Journal ref Extended Abstracts (Interactivity) of the 2024 CHI Conference on Human Factors in Computing Systems (CHI EA '24), Article 406, pp. 1-4

Epileptic Seizure Detection and Prediction from EEG Data: A Machine Learning Approach with Clinical Validation

Ria Jayanti, Tanish Jain

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

Comments 9 pages, 3 figures

Moderating Role of Presence in EEG Responses to Visuo-haptic Prediction Error in Virtual Reality

Lukas Gehrke, Leonie Terfurth, Klaus Gramann

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.HC

LUNA: Efficient and Topology-Agnostic Foundation Model for EEG Signal Analysis

Berkay Döner, Thorir Mar Ingolfsson, Luca Benini, Yawei Li

机构 * Integrated Systems Laboratory, ETH Zürich（瑞士苏黎世联邦理工学院集成系统实验室） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

Comments NeurIPS camera-ready version, 27 pages, 10 figures, 13 tables

EvoBrain: Dynamic Multi-Channel EEG Graph Modeling for Time-Evolving Brain Networks

Rikuto Kotoge, Zheng Chen, Tasuku Kimura, Yasuko Matsubara, Takufumi Yanagisawa, Haruhiko Kishima, Yasushi Sakurai

机构 * Department of Neurosurgery, Graduate School of Medicine, The University of Osaka, Japan（大阪大学医学研究生院神经外科） ； Institute for Advanced Co-Creation Studies, The University of Osaka, Japan（大阪大学先进协同研究机构） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

Comments Accepted by NeurIPS 2025 (spotlight)

Auditory Attention Decoding from Ear-EEG Signals: A Dataset with Dynamic Attention Switching and Rigorous Cross-Validation

Yuanming Zhang, Zeyan Song, Jing Lu, Fei Chen, Zhibin Lin

专题命中 EEG解码 ：EEG(title,abstract)；分类 eess.SP

EEG-Based Consumer Behaviour Prediction: An Exploration from Classical Machine Learning to Graph Neural Networks

Mohammad Parsa Afshar, Aryan Azimi

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

Automated Video-EEG Analysis in Epilepsy Studies: Advances and Challenges

Valerii A. Zuev, Elena G. Salmagambetova, Stepan N. Djakov, Lev V. Utkin

机构 * Peter the Great St.Petersburg Polytechnic University（彼得大帝圣彼得堡理工大学） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

FEMBA: Efficient and Scalable EEG Analysis with a Bidirectional Mamba Foundation Model

Anna Tegon, Thorir Mar Ingolfsson, Xiaying Wang, Luca Benini, Yawei Li

机构 * Integrated Systems Laboratory, ETH Zürich（瑞士苏黎世联邦理工学院集成系统实验室） ； DEI, University of Bologna（博洛尼亚大学DEI） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；分类 cs.LG

Comments 7 pages, 3 figures, 5 tables, Camera-ready version, EMBC 2025