脑机接口 / BCI

EEG-based Drowsiness Estimation for Driving Safety using Deep Q-Learning

Yurui Ming, Dongrui Wu, Yu-Kai Wang, Yuhui Shi, Chin-Teng Lin

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 eess.SP、cs.LG

Investigating EEG-Based Functional Connectivity Patterns for Multimodal Emotion Recognition

Xun Wu, Wei-Long Zheng, Bao-Liang Lu

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 cs.LG、cs.HC

Comments 15 pages, 11 figures

Offline EEG-Based Driver Drowsiness Estimation Using Enhanced Batch-Mode Active Learning (EBMAL) for Regression

Dongrui Wu, Vernon J. Lawhern, Stephen Gordon, Brent J. Lance, Chin-Teng Lin

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 cs.LG、cs.HC

Journal ref IEEE Int'l. Conf. on Systems, Man and Cybernetics, pp. 730-736, Budapest, Hungary, 2016

EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features

Dongrui Wu, Brent J. Lance, Vernon J. Lawhern, Stephen Gordon, Tzyy-Ping Jung, Chin-Teng Lin

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 cs.LG、cs.HC

Comments arXiv admin note: text overlap with arXiv:1702.02914

Journal ref IEEE Trans. on Neural Systems and Rehabilitation Engineering, 25(11), pp. 2157-2168, 2017

Universal EEG Encoder for Learning Diverse Intelligent Tasks

Baani Leen Kaur Jolly, Palash Aggrawal, Surabhi S Nath, Viresh Gupta, Manraj Singh Grover, Rajiv Ratn Shah

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain computer interface(abstract)；分类 eess.SP、cs.LG

Multi-channel EEG recordings during a sustained-attention driving task

Zehong Cao, Chun-Hsiang Chuang, Jung-Kai King, Chin-Teng Lin

专题命中 EEG解码 ：EEG(title,abstract)；brain computer interface(abstract)；cortical(abstract)；分类 q-bio.NC、eess.SP

Comments This manuscript is submitting to Nature: Scientific Data

Journal ref Scientific Data (volume 6, Article number: 19) (2019)

EEG-Based Driver Drowsiness Estimation Using Convolutional Neural Networks

Yuqi Cui, Dongrui Wu

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 cs.LG、cs.HC

Tensor-driven extraction of developmental features from varying paediatric EEG datasets

Eli Kinney-Lang, Loukianos Spyrou, Ahmed Ebied, Richard FM Chin, Javier Escudero

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 q-bio.NC、eess.SP

Comments 16 pages, 6 figures, pre-print, under consideration for publication. Reduced figure resolution due to size limit-please contact corresponding author for full figure resolution

Adaptive Stimulus Selection in ERP-Based Brain-Computer Interfaces by Maximizing Expected Discrimination Gain

Dmitry Kalika, Leslie M. Collins, Chandra S. Throckmorton, Boyla O. Mainsah

专题命中 EEG解码 ：brain-computer interface(title,abstract)；BCI(abstract)；EEG(abstract)；分类 q-bio.NC、cs.HC

Comments This paper has been accepted for the 2017 IEEE International Conference on Systems, Man and Cybernetics (SMC)

Head-related Impulse Response Cues for Spatial Auditory Brain-computer Interface

Chisaki Nakaizumi, Shoji Makino, Tomasz M. Rutkowski

专题命中 EEG解码 ：brain-computer interface(title,abstract)；BCI(abstract)；EEG(abstract)；分类 q-bio.NC、cs.HC

Comments 4 pages, 4 figures, accepted for EMBC 2015, IEEE copyright

Effects of Feedback Latency on P300-based Brain-computer Interface

Mahnaz Arvaneh, Tomas E. Ward, Ian H. Robertson

专题命中 EEG解码 ：brain-computer interface(title,abstract)；BCI(abstract)；EEG(abstract)；分类 q-bio.NC、cs.HC

Comments Accepted for publication in IEEE EMBC 2015

Images from the Mind: BCI image evolution based on Rapid Serial Visual Presentation of polygon primitives

Luís F. Seoane, Stephan Gabler, Benjamin Blankertz

专题命中 EEG解码 ：BCI(title,abstract)；brain-computer interface(abstract)；EEG(abstract)；分类 q-bio.NC、cs.HC

Comments 22 pages, 8 figures

Two-step Input Spatial Auditory BCI for Japanese Kana Characters

Moonjeong Chang, Tomasz M. Rutkowski

专题命中 EEG解码 ：BCI(title,abstract)；brain-computer interface(abstract)；EEG(abstract)；分类 q-bio.NC、cs.HC

Comments 7 pages, 2 figures, accepted for publication in Advances in Cognitive Neurodynamics Volume 5 -- Proceedings of the 5th International Conference on Cognitive Neurodynamics (ICCN 2015)

Vibrotactile Stimulus Frequency Optimization for the Haptic BCI Prototype

Hiromu Mori, Yoshihiro Matsumito, Shoji Makino, Victor Kryssanov, Tomasz M. Rutkowski

专题命中 EEG解码 ：BCI(title,abstract)；brain computer interface(abstract)；EEG(abstract)；分类 q-bio.NC、cs.HC

Comments The 6th International Conference on Soft Computing and Intelligent Systems and The 13th International Symposium on Advanced Intelligent Systems, 2012

Decoding Workload and Agreement From EEG During Spoken Dialogue With Conversational AI

从语音对话中解码工作负荷与共识的EEG信号

Lucija Mihić Zidar, Philipp Wicke, Praneel Bhatia, Rosa Lutz, Marius Klug, Thorsten O. Zander

机构 * Chair of Neuroadaptive Human--Computer Interaction（神经适应性人机交互教授席位） ； Brandenburg Technical University Cottbus--Senftenberg（勃兰登堡技术大学库滕堡-森芬根堡分校） ； Auryal GmbH（Auryal公司） ； Cottbus, Germany（库滕堡，德国） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；brain-computer interface(abstract,comments)；BCI(abstract)；分类 cs.HC

AI总结 本文提出通过EEG解码语音对话中的工作负荷与共识，验证了现有分类器在对话场景中的迁移能力，并探讨了其应用限制。

Comments Accepted at the 14th International Winter Conference on Brain-Computer Interface

Towards Scalable Handwriting Communication via EEG Decoding and Latent Embedding Integration

Jun-Young Kim, Deok-Seon Kim, Seo-Hyun Lee

专题命中 EEG解码 ：EEG(title,abstract)；brain-computer interface(abstract,comments)；neural signal(abstract)；分类 cs.LG

Comments 4 pages, 2 figures, 1 table, Name of Conference: International Conference on Brain-Computer Interface

Towards Neurohaptics: Brain-Computer Interfaces for Decoding Intuitive Sense of Touch

Jeong-Hyun Cho, Ji-Hoon Jeong, Myoung-Ki Kim, Seong-Whan Lee

专题命中 EEG解码 ：brain-computer interface(title,abstract)；BCI(abstract)；EEG(abstract)；分类 cs.HC

Comments Submitted IEEE The 9th International Winter Conference on Brain-Computer Interface

Domain Generalization for Session-Independent Brain-Computer Interface

Dong-Kyun Han, Ji-Hoon Jeong

专题命中 EEG解码 ：brain-computer interface(title,abstract)；BCI(abstract)；EEG(abstract)；分类 cs.HC

Comments Submitted IEEE The 9th International Winter Conference on Brain-Computer Interface

Versatile Framework with Semantic and Structural guidance for Image Reconstruction from Brain Activity

基于语义和结构引导的大脑活动图像重建通用框架

Yizhuo Lu, Changde Du, Qiongyi Zhou, Liuyun Jiang, Huiguang He

机构 * State Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology（脑认知与脑启发智能技术国家重点实验室） ； Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所） ； School of Future Technology, University of Chinese Academy of Sciences（中国科学院大学未来技术学院） ； School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院） 纠错

专题命中 EEG解码 ：EEG(summary_cn,abstract)；brain-computer interface(abstract)；neural decoding(abstract)

AI总结 提出MindDiffuser两阶段框架，结合CLIP文本嵌入和视觉特征，通过Stable Diffusion生成语义图像并迭代优化结构信息，在fMRI、EEG、MEG三种模态上显著提升图像重建性能。

Predicting Artificial Neural Network Representations to Learn Recognition Model for Music Identification from Brain Recordings

Taketo Akama, Zhuohao Zhang, Pengcheng Li, Kotaro Hongo, Hiroaki Kitano, Shun Minamikawa, Natalia Polouliakh

专题命中 EEG解码 ：BCI(abstract)；brain-computer interface(abstract)；EEG(abstract)；neural decoding(abstract)

Comments 18 pages, 10 figures

Subliminal Probing for Private Information via EEG-Based BCI Devices

Mario Frank, Tiffany Hwu, Sakshi Jain, Robert Knight, Ivan Martinovic, Prateek Mittal, Daniele Perito, Dawn Song

专题命中 EEG解码 ：BCI(title,abstract)；EEG(title)

Comments under review for a journal publication

Physiological Prior-Driven Label Enhancement for Cross-Subject EEG Emotion Recognition

用于跨主体脑电情感识别的生理先验驱动标签增强

Hongyu Zhu, Lin Chen, Yuming Fu, Mounim A. El-Yacoubi, Mingsheng Shang

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

AI总结 针对跨主体脑电情感识别中标签噪声问题，提出PhyDA框架，通过生理噪声量化器和数据自适应标签细化器，统一神经生理先验与数据驱动的标签细化，实验证明该方法显著优于基线，具有可解释性和鲁棒性。

Comments Submitted; 11 pages

Aperiodic and Low-Frequency Spectral Bias in Reconstruction based EEG Foundation Models

基于重建的脑电图基础模型中的非周期和低频谱偏差

Aditya Kommineni, Emily Zhou, Kleanthis Avramidis, Simon Bock Segaard, Jeppe Roden Münster, Andreas Peter Juhl Hansen, Takfarinas Medani, Tiantian Feng, Richard Leahy, Shrikanth Narayanan

机构 * University of Southern California（美国南加州大学） ； Aalborg University（奥尔堡大学） 纠错

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

AI总结 研究揭示基于重建预训练的脑电图基础模型存在非周期和低频成分偏差，导致低资源场景下性能不佳，并提出通过辅助损失关注高频振荡结构来改进。

Comments 18 pages, 13 figures, 3 tables

BandVQ: Band-Wise Vector-Quantized EEG Foundation Model

BandVQ: 分带向量量化的脑电图基础模型

Jamiyan Sukhbaatar, Satoshi Imamura, Toshihisa Tanaka

机构 * Tokyo University of Agriculture and Technology（东京农工大学） ； National University of Mongolia（蒙古国国立大学） 纠错

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

AI总结 针对脑电图基础模型中频率特异性活动表征不足的问题，提出BandVQ模型，通过分带VQ-VAE分词器和共享Transformer编码器，在71个公共数据集上预训练，并在六个分类任务上取得领先性能。

Comments 15 pages, 1 figure

LI-DSN: A Layer-wise Interactive Dual-Stream Network for EEG Decoding

LI-DSN：一种分层交互双流网络用于EEG解码

Chenghao Yue, Zhiyuan Ma, Zhongye Xia, Xinche Zhang, Yisi Zhang, Xinke Shen, Sen Song

机构 * School of Biomedical Engineering, Tsinghua Laboratory of Brain and Intelligence, and IDG/McGovern Institute for Brain Research, Tsinghua University（清华大学生物医学工程学院、清华脑与智能实验室、IDG/麦戈文脑科学研究院） ； School of Life Sciences, Tsinghua University（清华大学生命科学学院） ； Department of Biomedical Engineering, Southern University of Science and Technology（南方科技大学生物医学工程系） ； Department of Psychological and Cognitive Sciences, Tsinghua University（清华大学心理与认知科学系） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；brain-computer interface(abstract)；motor imagery(abstract)；分类 cs.LG

AI总结 本文提出LI-DSN，通过分层交互机制解决双流网络中信息孤岛问题，引入TSIA机制和自适应融合策略，在八个EEG数据集上验证其优越的解码性能。

BiMoE: Brain-Inspired Experts for EEG-Dominant Affective State Recognition

BiMoE：受脑启发的专家用于EEG主导的情感状态识别

Hongyu Zhu, Lin Chen, Mingsheng Shang

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 cs.HC

AI总结 BiMoE通过脑拓扑感知划分EEG信号，利用双流编码器提取局部和全局时空特征，结合多尺度大核卷积处理PPS，动态融合专家并通过联合损失函数提升多模态情感分类性能。

Comments Accepted by ICME 2026

EEG-Based Brain-LLM Interface for Human Preference Aligned Generation

基于EEG的脑-大语言模型接口用于人类偏好对齐生成

Junzi Zhang, Jianing Shen, Weijie Tu, Yi Zhang, Hailin Zhang, Tom Gedeon, Bin Jiang, Yue Yao

机构 * Shandong University, China（山东大学） ； Australian National University, Australia（澳大利亚国立大学） ； Curtin University, Australia（Curtin大学） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；neural signal(abstract)；分类 q-bio.NC、eess.SP、cs.LG

AI总结 本文提出基于EEG的脑-大语言模型接口，通过EEG信号引导图像生成模型，利用神经信号反馈实现模型动态适应，为适应性语言模型推理提供新思路。

Comments 15 pages, 9 figures

Learning Domain- and Class-Disentangled Prototypes for Domain-Generalized EEG Emotion Recognition

学习领域和类别解耦的原型以实现领域通用的EEG情绪识别

Guangli Li, Canbiao Wu, Zhehao Zhou, Na Tian, Li Zhang, Zhen Liang

机构 * School of Biological Science and Medical Engineering, Hunan University of Technology（湖南理工大学生物科学与医学工程学院） ； School of Biomedical Engineering, Health Science Center, Shenzhen University（深圳大学生物医学工程学院） ； Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging（广东省生物医学测量与超声成像重点实验室） ； Shenzhen Pengrui Brain Science Technology（深圳鹏瑞脑科学科技） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 cs.LG

AI总结 本文提出MAT框架，通过解耦领域和类别特征，提升EEG情绪识别在未知目标领域的鲁棒性和可解释性，实验显示在三个公开数据集上准确率提升2.87%-3.84%。

Deep Convolutional Architectures for EEG Classification: A Comparative Study with Temporal Augmentation and Confidence-Based Voting

用于EEG分类的深度卷积架构：带有时间增强和基于置信度的投票的比较研究

Aryan Patodiya, Hubert Cecotti

机构 * Department of Computer Science（计算机科学系） ； California State University, Fresno（加州州立大学，弗雷斯诺分校） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 cs.LG

AI总结 本文比较了深度学习架构在EEG信号分类中的应用，通过时间增强和置信度投票机制提升分类性能，发现3D CNN在AUC和平衡准确率上优于2D架构。

Comments 14 pages, 8 figures, Recent Trends in Image Processing and Pattern Recognition, Copyright held by Springer CCIS

A Temporal-Spectral Fusion Transformer with Subject-Specific Adapter for Enhancing RSVP-BCI Decoding

具有主体特定适配器的时序-频谱融合变换器用于增强RSVP-BCI解码

Xujin Li, Wei Wei, Shuang Qiu, Huiguang He

专题命中 EEG解码 ：BCI(title,abstract)；brain-computer interface(abstract)；EEG(abstract)；分类 cs.HC

AI总结 本文提出TSformer-SA，通过时序-频谱融合和主体特定适配器提升RSVP-BCI解码性能，减少训练时间。

Comments 19 pages, 10 figures

Journal ref Neural Networks, 2025, 181: 106844