脑机接口 / BCI

On the utility of power spectral techniques with feature selection techniques for effective mental task classification in noninvasive BCI

Akshansh Gupta, Ramesh Kumar Agrawal, Jyoti Singh Kirar, Javier Andreu-Perez, Wei-Ping Ding, Chin-Teng Lin, Mukesh Prasad

专题命中 BCI数据与评测 ：BCI(title,abstract)；brain-computer interface(abstract)；分类 q-bio.NC、eess.SP、cs.LG

Journal ref IEEE Transactions on Systems, Man, and Cybernetics: Systems 51.5 (2019): 3080-3092

Cross-Subject Transfer Learning Improves the Practicality of Real-World Applications of Brain-Computer Interfaces

Kuan-Jung Chiang, Chun-Shu Wei, Masaki Nakanishi, Tzyy-Ping Jung

专题命中 BCI数据与评测 ：brain-computer interface(title,abstract)；BCI(abstract)；分类 q-bio.NC、eess.SP、cs.LG

Comments 4 pages, 3 figures, 1 table. For NER'19

A Consumer BCI for Automated Music Evaluation Within a Popular On-Demand Music Streaming Service - Taking Listener's Brainwaves to Extremes

Fotis Kalaganis, Dimitrios A. Adamos, Nikos Laskaris

专题命中 BCI数据与评测 ：BCI(title,abstract)；brain computer interface(abstract)；EEG(abstract)；分类 cs.HC

Comments 12th IFIP WG 12.5 International Conference and Workshops, AIAI 2016, Thessaloniki, Greece, September 16-18, 2016, Proceedings

Journal ref Artificial Intelligence Applications and Innovations, Volume 475 of the series IFIP Advances in Information and Communication Technology pp 429-440, 2016

Threat Vectors and the State of the Art in Defense Methods for Security in Neurotechnology

神经技术安全防御方法中的威胁向量与现状

Bryce-Allen Bagley, Nathaniel Rose, Quintus Kilbourn, Matthew Canham

专题命中 BCI数据与评测 ：BCI(summary_cn,abstract)；brain-computer interface(abstract)；分类 q-bio.NC、cs.HC

AI总结 本文针对脑机接口安全研发滞后问题，回顾神经安全技术现状，全面调查BCI系统安全威胁，给出可应用于弥补神经安全差距的现有方法建议，助力提升神经技术安全。

Exploring new territory: Calibration-free decoding for c-VEP BCI

J. Thielen, J. Sosulski, M. Tangermann

专题命中 BCI数据与评测 ：BCI(title,abstract)；brain-computer interface(abstract,comments)；分类 eess.SP、cs.LG

Comments 6 pages, 2 figures, 9th Graz Brain-Computer Interface Conference 2024

Journal ref 9th Graz Brain-Computer Interface Conference (2024) 325-330

Leveraging Transfer Learning and User-Specific Updates for Rapid Training of BCI Decoders

Ziheng Chen, Po T. Wang, Mina Ibrahim, Shivali Baveja, Rong Mu, An H. Do, Zoran Nenadic

专题命中 BCI数据与评测 ：BCI(title,abstract)；brain-computer interface(abstract)；EEG(abstract)

Comments 6 page conference proceeding preprint

High-performance cVEP-BCI under minimal calibration

Yining Miao, Nanlin Shi, Changxing Huang, Yonghao Song, Xiaogang Chen, Yijun Wang, Xiaorong Gao

专题命中 BCI数据与评测 ：BCI(title,abstract)；brain-computer interface(abstract)；分类 q-bio.NC、eess.SP、cs.HC

Comments 35 pages, 5 figures

A Novel Semi-supervised Meta Learning Method for Subject-transfer Brain-computer Interface

Jingcong Li, Fei Wang, Haiyun Huang, Feifei Qi, Jiahui Pan

专题命中 BCI数据与评测 ：brain-computer interface(title,abstract)；BCI(abstract)；分类 eess.SP、cs.LG、cs.HC

Team Cogitat at NeurIPS 2021: Benchmarks for EEG Transfer Learning Competition

Stylianos Bakas, Siegfried Ludwig, Konstantinos Barmpas, Mehdi Bahri, Yannis Panagakis, Nikolaos Laskaris, Dimitrios A. Adamos, Stefanos Zafeiriou

专题命中 BCI数据与评测 ：EEG(title,abstract)；motor imagery(abstract)；分类 eess.SP、cs.LG、cs.HC

Student Teaching and Research Laboratory Focusing on Brain-computer Interface Paradigms - A Creative Environment for Computer Science Students -

Tomasz M. Rutkowski

专题命中 BCI数据与评测 ：brain-computer interface(title,abstract)；BCI(abstract)；分类 q-bio.NC、cs.HC、cs.RO

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

Zero-calibration cVEP BCI using word prediction: a proof of concept

Federica Turi, Nathalie Gayraud, Maureen Clerc

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

Comments BCI 2018 - 7th International BCI Meeting, May 2018, Pacific Grove, California, United States

Learning from Label Proportions in Brain-Computer Interfaces: Online Unsupervised Learning with Guarantees

D Hübner, T Verhoeven, K Schmid, K-R Müller, M Tangermann, P-J Kindermans

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

Comments The EEG data of 13 subjects is freely available online at: http://doi.org/10.5281/zenodo.192684

Transfer Learning in Brain-Computer Interfaces

Vinay Jayaram, Morteza Alamgir, Yasemin Altun, Bernhard Schölkopf, Moritz Grosse-Wentrup

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

Comments To be published in IEEE Computational Intelligence Magazine, special BCI issue on January 15th online

Airborne Ultrasonic Tactile Display BCI

Katsuhiko Hamada, Hiromu Mori, Hiroyuki Shinoda, Tomasz M. Rutkowski

专题命中 BCI数据与评测 ：BCI(title,abstract)；brain computer interface(abstract)；分类 q-bio.NC、cs.HC；brain-computer interface(journal_ref)

Comments arXiv admin note: substantial text overlap with arXiv:1404.4184

Journal ref Brain-Computer Interface Research - A State-of-the-Art Summary 4. SpringerBriefs in Electrical and Computer Engineering. 2015. p. 57-65

Airborne Ultrasonic Tactile Display Brain-computer Interface Paradigm

Katsuhiko Hamada, Hiromu Mori, Hiroyuki Shinoda, Tomasz M. Rutkowski

专题命中 BCI数据与评测 ：brain-computer interface(title,comments)；BCI(abstract)；brain computer interface(abstract)；分类 q-bio.NC、cs.HC

Comments 5 pages, 3 figures, submitted to 6th International Brain-Computer Interface Conference 2014, Graz, Austria

SSAS: Cross-subject EEG-based Emotion Recognition through Source Selection with Adversarial Strategy

SSAS: 通过对抗策略进行源选择的跨主体基于EEG的情感识别

Yici Liu, Qi Wei Oung, Hoi Leong Lee

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

AI总结 本文提出一种通过源选择与对抗策略进行的跨主体基于EEG的情感识别方法，旨在解决个体间变异性及负迁移问题，提升分类性能。

Comments Accepted by Expert Systems With Applications

HEDN: A Hard-Easy Dual Network with Source Reliability Assessment for Cross-Subject EEG Emotion Recognition

HEDN：一种具有源可靠性评估的硬易双网络用于跨受体EEG情绪识别

Qiang Wang, Liying Yang, Jiayun Song, Yifan Bai, Jingtao Du

机构 * School of Computer Science and Technology, Xidian University（电子科技大学计算机科学与技术学院） 纠错

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

AI总结 HEDN通过引入源可靠性评估机制，提出了一种轻量级的多源域适应框架，有效提升跨受体EEG情绪识别的性能与效率。

Comments This work has been submitted to the IEEE for possible publication

Cross-Subject and Cross-Montage EEG Transfer Learning via Individual Tangent Space Alignment and Spatial-Riemannian Feature Fusion

Nicole Lai-Tan, Xiao Gu, Marios G. Philiastides, Fani Deligianni

机构 * UKRI Centre for Doctoral Training in Socially Intelligent Artificial Agents（UKRI社会智能人工代理博士培训中心） ； EPSRC（工程与物理科学研究委员会） ； Academy of Medical Sciences（医学科学院） 纠错

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

Comments 12 pages, 5 figures

Tailoring deep learning for real-time brain-computer interfaces: From offline models to calibration-free online decoding

Martin Wimpff, Jan Zerfowski, Bin Yang

机构 * Institute of Signal Processing and System Theory, University of Stuttgart（信号处理与系统理论研究所，斯图加特大学） ； Clinical Neurotechnology Laboratory, Department of Psychiatry and Neurosciences, Charité Campus Mitte (CCM), Charité - Universitätsmedizin Berlin（临床神经技术实验室，精神病学与神经科学系，Charité-柏林大学医学院） 纠错

专题命中 BCI数据与评测 ：brain-computer interface(title,abstract)；BCI(abstract)；分类 cs.LG、cs.HC

M3D: Manifold-based Domain Adaptation with Dynamic Distribution for Non-Deep Transfer Learning in Cross-subject and Cross-session EEG-based Emotion Recognition

Ting Luo, Jing Zhang, Yingwei Qiu, Li Zhang, Yaohua Hu, Zhuliang Yu, Zhen Liang

机构 * School of Biomedical Engineering, Medical School, Shenzhen University（生物医学工程学院，医学学院，深圳大学） ； School of Public Health, Shenzhen University Medical School（公共卫生学院，深圳大学医学学院） ； Department of Radiology, Nanshan Hospital of Shenzhen University（放射科，深圳大学南山医院） ； School of Mathematical Sciences, Shenzhen University（数学科学学院，深圳大学） ； Shien-Ming Wu School of Intelligent Engineering, South China University of Technology（申明武智能工程学院，华南理工大学） ； Institute for Super Robotics, Guangzhou, Guangdong, China（超机器人研究所，广州，广东，中国） 纠错

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

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data

Christian Flores, Marcelo Contreras, Ichiro Macedo, Javier Andreu-Perez

专题命中 BCI数据与评测 ：BCI(title,abstract)；brain-computer interface(abstract)；分类 eess.SP、cs.LG

Journal ref IEEE Trans Neural Syst Rehabil Eng. 2024;32:3794-3803

Source Data Selection for Brain-Computer Interfaces based on Simple Features

Frida Heskebeck, Carolina Bergeling, Bo Bernhardsson

专题命中 BCI数据与评测 ：brain-computer interface(title,abstract)；motor imagery(abstract)；分类 cs.LG、cs.HC

Comments 10 pages, 3 figures, This work has been submitted to the IEEE for possible publication

BDAN: Mitigating Temporal Difference Across Electrodes in Cross-Subject Motor Imagery Classification via Generative Bridging Domain

Zhige Chen, Rui Yang, Mengjie Huang, Chengxuan Qin, Zidong Wang

专题命中 BCI数据与评测 ：motor imagery(title,abstract)；EEG(abstract)；分类 cs.LG、cs.HC

Emotion Detection from EEG using Transfer Learning

Sidharth Sidharth, Ashish Abraham Samuel, Ranjana H, Jerrin Thomas Panachakel, Sana Parveen K

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

Comments Preprint of the manuscript accepted for presentation in 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. DOI will be updated soon

Journal ref 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

Explainable artificial intelligence approaches for brain-computer interfaces: a review and design space

Param Rajpura, Hubert Cecotti, Yogesh Kumar Meena

专题命中 BCI数据与评测 ：brain-computer interface(title,abstract)；BCI(abstract)；分类 cs.LG、cs.HC

Comments draft submission

Introducing Block-Toeplitz Covariance Matrices to Remaster Linear Discriminant Analysis for Event-related Potential Brain-computer Interfaces

Jan Sosulski, Michael Tangermann

专题命中 BCI数据与评测 ：brain-computer interface(title,abstract)；BCI(abstract)；分类 q-bio.NC、cs.LG

Comments Updated references, changed layout

BCI decoder performance comparison of an LSTM recurrent neural network and a Kalman filter in retrospective simulation

Tommy Hosman, Marco Vilela, Daniel Milstein, Jessica N. Kelemen, David M. Brandman, Leigh R. Hochberg, John D. Simeral

专题命中 BCI数据与评测 ：BCI(title)；brain computer interface(abstract)；cortical(abstract)；分类 cs.LG、cs.HC

Comments Accepted for the 9th International IEEE EMBS Conference on Neural Engineering

The Influence of Decoding Accuracy on Perceived Control: A Simulated BCI Study

Pouyan R. Fard, Moritz Grosse-Wentrup

专题命中 BCI数据与评测 ：BCI(title,abstract)；brain-computer interface(abstract)；分类 q-bio.NC、cs.HC

ASPEN: Spectral-Temporal Fusion for Cross-Subject Brain Decoding

ASPEN：跨受试者脑解码的频谱-时间融合

Megan Lee, Seung Ha Hwang, Inhyeok Choi, Shreyas Darade, Mengchun Zhang, Kateryna Shapovalenko

机构 * Carnegie Mellon University（卡内基梅隆大学） ； Kyung Hee University（Kyung Hee大学） ； Korea Advanced Institute of Science and Technology（韩国科学技术院） ； University of Pittsburgh（匹兹堡大学） 纠错

专题命中 BCI数据与评测 ：brain-computer interface(abstract)；EEG(abstract)；neural signal(abstract)；motor imagery(abstract)

AI总结 ASPEN通过频谱-时间融合实现跨受试者脑解码，利用乘法融合提升跨模态一致性，有效提升未见受试者准确率。

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition

PRISM: 基于优先级通道重要性与半监督域适应的跨被试脑电情绪识别

Xin Zhou, Xiang Zhang, Hao Deng, Lijun Yin

机构 * School of Computing, T. J Watson College of Engineering and Applied Science, Binghamton University - State University of New York（计算学院、T.J Watson工程与应用科学学院、宾夕法尼亚州立大学宾夕法尼亚州立大学） 纠错

专题命中 BCI数据与评测 ：EEG(title,abstract)；分类 cs.LG

AI总结 提出PRISM框架，通过可微分通道加权和置信度过滤伪标签的半监督域适应，解决脑电情绪识别中的通道冗余和跨被试差异问题，在三个数据集上超越现有方法。