脑机接口 / BCI

An Improved EEG Acquisition Protocol Facilitates Localized Neural Activation

Jerrin Thomas Panachakel, Nandagopal Netrakanti Vinayak, Maanvi Nunna, A. G. Ramakrishnan, Kanishka Sharma

专题命中 EEG解码 ：EEG(title,abstract)；motor imagery(abstract)；分类 q-bio.NC、eess.SP

Comments Preprint of the paper presented at ComNet 2019

A Novel Deep Learning Architecture for Decoding Imagined Speech from EEG

Jerrin Thomas Panachakel, A. G. Ramakrishnan, T. V. Ananthapadmanabha

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

Comments Preprint of the paper presented at IEEE AIBEC 2019, Austria

Decoding Visual Responses based on Deep Neural Networks with Ear-EEG Signals

Young-Eun Lee, Minji Lee

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

Comments 6 pages, 3 figures, conference

Classification of EEG Signal based on non-Gaussian Neutral Vector

Zhanyu Ma

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

Comments Technical Report

Differences in MEG and EEG power-law scaling explained by a coupling between spatial coherence and frequency: a simulation study

Christian-G. Bénar, C. Grova, V. Jirsa, J. Lina

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

Journal ref Journal of Computational Neuroscience, Springer Verlag, 2019, 47 (1), pp.31-41

Prediction of Reaction Time and Vigilance Variability from Spatiospectral Features of Resting-State EEG in a Long Sustained Attention Task

Mastaneh Torkamani-Azar, Sumeyra Demir Kanik, Serap Aydin, Mujdat Cetin

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

Comments 11 pages, 6 figures; submitted to the Journal of Biomedical and Health Informatics

Multi-subject MEG/EEG source imaging with sparse multi-task regression

Hicham Janati, Thomas Bazeille, Bertrand Thirion, Marco Cuturi, Alexandre Gramfort

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

Comments version 2. arXiv admin note: text overlap with arXiv:1902.04812

EEG-Based Driver Drowsiness Estimation Using Feature Weighted Episodic Training

Yuqi Cuui, Yifan Xu, Dongrui Wu

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

Applying Transfer Learning To Deep Learned Models For EEG Analysis

Axel Uran, Coert van Gemeren, Rosanne van Diepen, Ricardo Chavarriaga, José del R. Millán

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

Comments 14 pages, 6 figures

Building Brain Invaders: EEG data of an experimental validation

Gijsbrecht Van Veen, Alexandre Barachant, Anton Andreev, Grégoire Cattan, Pedro Coelho Rodrigues, Marco Congedo

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

Comments arXiv admin note: substantial text overlap with arXiv:1904.09111

A Real-time Control Approach for Unmanned Aerial Vehicles using Brain-computer Interface

Ravi M. Vishwanath, Saumya Kumaar, S N Omkar

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

Comments 7 pages

Directional and Causal Information Flow in EEG for Assessing Perceived Audio Quality

Ketan Mehta, Joerg Kliewer

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

Comments IEEE Transactions on Molecular, Biological, and Multi-Scale Communication, September 2017, Vol. 3

Switching EEG Headsets Made Easy: Reducing Offline Calibration Effort Using Active Weighted Adaptation Regularization

Dongrui Wu, Vernon J. Lawhern, W. David Hairston, Brent J. Lance

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

Journal ref IEEE Trans. on Neural Systems and Rehabilitation Engineering, 24(11), pp. 1125-1137 (2016)

Towards the bio-personalization of music recommendation systems: A single-sensor EEG biomarker of subjective music preference

Dimitrios A. Adamos, Stavros I. Dimitriadis, Nikolaos A. Laskaris

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

Journal ref Information Sciences, Volumes 343 - 344, 20 May 2016, Pages 94 - 108

Bio-Inspired Filter Banks for SSVEP-based Brain-Computer Interfaces

A. Fatih Demir, Huseyin Arslan, Ismail Uysal

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

Comments 2016 IEEE International Conference on Biomedical and Health Informatics (BHI)

Journal ref 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), Feb. 2016, pp. 144-147

Novel Virtual Moving Sound-based Spatial Auditory Brain-Computer Interface Paradigm

Yohann Lelievre, Tomasz M. Rutkowski

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

Comments 4 pages (in conference proceedings original version); 6 figures, accepted at 6th International IEEE EMBS Conference on Neural Engineering, November 6-8, 2013, Sheraton San Diego Hotel & Marina, San Diego, CA; paper ID 465; to be available at IEEE Xplore; IEEE Copyright 2013

Journal ref Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on. IEEE Engineering in Medicine and Biology Society; 2013. p. 9-12

Auditory Brain-Computer Interface Paradigm with Head Related Impulse Response-based Spatial Cues

Chisaki Nakaizumi, Koichi Mori, Toshie Matsui, Shoji Makino, Tomasz M. Rutkowski

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

Comments The final publication is available at IEEE Xplore http://ieeexplore.ieee.org and the copyright of the final version has been transferred to IEEE (c)2013

Journal ref Proceedings of the 9th International Conference on Signal Image Technology and Internet Based Systems. Kyoto, Japan: IEEE Computer Society; 2013. p. 806-811

Haptic BCI Paradigm based on Somatosensory Evoked Potential

Tomasz M. Rutkowski, Hiromu Mori, Yoshihiro Matsumoto, Zhenyu Cai, Moonjeong Chang, Nozomu Nishikawa, Shoji Makino, Koichi Mori

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

Comments 2 pages, 1 figure

Psychophysical Responses Comparison in Spatial Visual, Audiovisual, and Auditory BCI-Spelling Paradigms

Moonjeong Chang, Nozomu Nishikawa, Zhenyu Cai, Shoji Makino, Tomasz M. Rutkowski

专题命中 EEG解码 ：BCI(title,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

Auditory Steady-State Response Stimuli based BCI Application - The Optimization of the Stimuli Types and Lengths

Yoshihiro Matsumoto, Nozomu Nishikawa, Takeshi Yamada, Shoji Makino, Tomasz M. Rutkowski

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

Comments APSIPA ASC 2012

Prototype-Guided Non-Exemplar Continual Learning for Cross-subject EEG Decoding

基于原型的非示例持续学习用于跨受体EEG解码

Dan Li, Hye-Bin Shin, Yeon-Woo Choi

机构 * Dept. of Artificial Intelligence Korea University Seoul, Republic of Korea（人工智能系 韩国大学首尔共和国） ； Cognitive Engineering Korea University Seoul, Republic of Korea（认知工程 韩国大学首尔共和国） 纠错

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

AI总结 ProNECL通过原型引导的非示例持续学习方法，在不访问历史EEG样本的情况下实现跨个体EEG解码的高效知识保留与适应性平衡。

Comments 4 pages, 2 figures, 14th IEEE International Winter Conference on Brain-Computer Interface Conference 2026

Deep Learning Classification of EEG Responses to Multi-Dimensional Transcranial Electrical Stimulation

基于多维经颅电刺激的深度学习EEG分类

Alexis Pomares Pastor, Ines Ribeiro Violante, Gregory Scott

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

AI总结 本研究利用深度学习对EEG信号进行分类，通过多维经颅电刺激评估意识状态，实现了92%的分类准确率，超越人类水平。

Comments For open-sourced datasets and source code, see: https://github.com/alexispomares/DL-EEG-TES

EEG-Reptile: An Automatized Reptile-Based Meta-Learning Library for BCIs

Daniil A. Berdyshev, Artem M. Grachev, Sergei L. Shishkin, Bogdan L. Kozyrskiy

机构 * MEG Center, Moscow State University of Psychology and Education（莫斯科心理与教育大学MEG中心） ； Lomonosov Moscow State University（莫斯科罗蒙诺索夫大学） 纠错

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

Comments For proposed python library, see EEG-Reptile GitHub: https://github.com/gasiki/EEG-Reptile Changes: minor edits in introduction and references

Understanding data analysis aspects of TMS-EEG in clinical study: a mini review and a case study with open dataset

Hua Cheng

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

Comments 39 pages,36 fighures,TMS-EEG data analysis

Decoding 3D Representation of Visual Imagery EEG using Attention-based Dual-Stream Convolutional Neural Network

Hyung-Ju Ahn, Dae-Hyeok Lee

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

Comments Submitted to 2022 10th IEEE International Winter Conference on Brain-Computer Interface

Decoding Event-related Potential from Ear-EEG Signals based on Ensemble Convolutional Neural Networks in Ambulatory Environment

Young-Eun Lee, Seong-Whan Lee

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

Comments Submitted IEEE the 9th International Winter Conference on Brain-Computer Interface. arXiv admin note: text overlap with arXiv:2002.01085

An Ensemble Learning Based Classification of Individual Finger Movement from EEG

Sutanu Bera, Rinku Roy, Debdeep Sikdar, Manjunatha Mahadevappa

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

Comments Brain Computer Interfacing, EEG, Finger movement analysis

Beyond Local Power: Functional Connectivity Analysis for Subject-Independent Learning Style Recognition

超越局部能力：用于被试独立学习风格识别的功能连接分析

Wiga Maulana Baihaqi, Indriana Hidayah, Sri Kusrohmaniah, Noor Akhmad Setiawan

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

AI总结 该研究提出基于EEG和PLV连接性的方法，识别被试独立学习风格，在VV维度获70.00%准确率，AR维度仅55.56%，指出需自适应特征变换缩小跨被试泛化差距。

Comments 7 pages, 5 figures. Accepted for publication at 4th IEEE International Conference on Artificial Intelligence and Mechatronics Systems 2026

A Quantum Reservoir for Neurodynamical Forecasting

用于神经动力学预测的量子储备池

Annemarie Wolff, Kathleen Hamilton, Kahn Rhrissorrakrai, Laxmi Parida, Filippo Utro, Guillaume Dumas

专题命中 EEG解码 ：EEG(summary_cn,abstract)；neural signal(abstract)

AI总结 该研究探究量子储备池计算（QRC）在神经动力学预测中的表现，构建基于横场伊辛模型的量子储备池，在基准任务与模拟EEG数据上验证其可行性，为量子系统用于临床时间序列预测建立了实用基线。

Comments 7 pages (including references), 2 figures, Accepted at IEEE Quantum Week (QCE 2026) short technical paper, Applications category

Journal ref Proc. IEEE Int. Conf. Quantum Comput. Eng. (QCE), 2026

MultiDiffNet: A Multi-Objective Diffusion Framework for Generalizable Brain Decoding

MultiDiffNet: 一种面向通用脑解码的多目标扩散框架

Mengchun Zhang, Kateryna Shapovalenko, Yucheng Shao, Eddie Guo, Parusha Pradhan

机构 * University of Pittsburgh（匹兹堡大学） ； Carnegie Mellon University（卡内基梅隆大学） 纠错

专题命中 EEG解码 ：BCI(abstract)；EEG(abstract)；neural decoding(abstract)；motor imagery(abstract)

AI总结 MultiDiffNet通过多目标扩散框架实现通用脑电解码，提供统一基准测试和统计报告框架，提升跨受试者泛化能力。