脑机接口 / BCI

Speed-enhanced Subdomain Adaptation Regression for Long-term Stable Neural Decoding in Brain-computer Interfaces

Jiyu Wei, Dazhong Rong, Xinyun Zhu, Qinming He, Yueming Wang

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

EEG-DG: A Multi-Source Domain Generalization Framework for Motor Imagery EEG Classification

Xiao-Cong Zhong, Qisong Wang, Dan Liu, Zhihuang Chen, Jing-Xiao Liao, Jinwei Sun, Yudong Zhang, Feng-Lei Fan

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

End-to-End Deep Transfer Learning for Calibration-free Motor Imagery Brain Computer Interfaces

Maryam Alimardani, Steven Kocken, Nikki Leeuwis

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

Revisiting Euclidean Alignment for Transfer Learning in EEG-Based Brain-Computer Interfaces

Dongrui Wu

机构 * Ministry of Education Key Laboratory of Image Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan, 430074 China（教育部长图像处理与智能控制重点实验室，华中科技大学，武汉，430074中国） ； Zhongguancun Academy, Beijing, 100084 China（中关村学院，北京，100084中国） 纠错

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

Journal ref Journal of Neural Engineering, 22: 031005, 2025

Subject-Adaptive Transfer Learning Using Resting State EEG Signals for Cross-Subject EEG Motor Imagery Classification

Sion An, Myeongkyun Kang, Soopil Kim, Philip Chikontwe, Li Shen, Sang Hyun Park

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

Comments Early Accepted at MICCAI 2024

BCIJelly: An integrated ecosystem for brain-computer interface research

BCIJelly：用于脑机接口研究的集成生态系统

Liyuan Han, Xinrui Yang, Tianyu Zheng, Qizhi Yang, Yitao Qin, Liang Chen, Qinglai Wei, Binjie Hong, Xinhe Zhang, Rui Xiong, Yong Gu, Mu-ming Poo, Bo Xu, Chengyu Li, Tielin Zhang

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

AI总结 BCIJelly是集成多类BCI数据集、解码器及工具的Python生态系统，可通过AAS与LLM支持多任务跨物种解码，经多范式多物种验证，为BCI研究提供统一可扩展的开发部署基础设施。

Comments 67 pages, 6 figures, 7 extended data figures, 20 supplementary tables

Fuzzy normed BCK-algebras and BCI-algebras

模糊赋范BCK-代数和BCI-代数

Young Bae Jun, Ravikumar Bandaru

专题命中 BCI数据与评测 ：BCI(title,title_cn)

AI总结 将经典赋范代数结构推广到模糊环境，引入模糊赋范BCK/BCI-代数，建立基本性质并研究同态下的传递条件。

Dimensionality reduction based on Distance Preservation to Local Mean (DPLM) for SPD matrices and its application in BCI

基于距离保持到局部均值的距离降维（DPLM）的SPD矩阵及其在BCI中的应用

Alireza Davoudi, Saeed Shiry Ghidary, Khadijeh Sadatnejad

专题命中 BCI数据与评测 ：BCI(title,title_cn)

AI总结 本文提出了一种非线性降维算法，用于对对称正定（SPD）矩阵流形进行处理，通过保持数据的局部结构和局部均值距离（DPLM）来提供高类间区分的低维表示。实验表明，DPLM在BCI竞赛IV的多类数据集IIa上优于其他方法，因其对异常值具有鲁棒性。

Integrating Language-Image Prior into EEG Decoding for Cross-Task Zero-Calibration RSVP-BCI

将语言-图像先验整合到EEG解码中以实现跨任务零校准RSVP-BCI

Xujin Li, Wei Wei, Shuang Qiu, Xinyi Zhang, Fu Li, Huiguang He

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

AI总结 本研究提出ELIPformer模型，通过融合语言-图像先验知识提升跨任务零校准RSVP-BCI的解码性能。

Comments 15 pages, 11 figures

Journal ref Machine Intelligence Research (2026)

Inter-subject Deep Transfer Learning for Motor Imagery EEG Decoding

Xiaoxi Wei, Pablo Ortega, A. Aldo Faisal

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

Comments Accepted manuscript IEEE/EMBS Neural Engineering (NER) 2021

Evaluation of Motor Imagery-Based BCI methods in neurorehabilitation of Parkinson's Disease patients

Aleksandar Miladinović, Miloš Ajčević, Pierpaolo Busan, Joanna Jarmolowska, Giulia Silveri, Manuela Deodato, Sussana Mezzarobba, Piero Paolo Battaglini, Agostino Accardo

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

Journal ref 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

OmniEEG-Bench: A Standardized Evaluation Benchmark for EEG Foundation Models

OmniEEG-Bench: 脑电图基础模型的标准化评估基准

Ziling Lu, Zongsheng Li, Xinke Shen, Kexin Lou, Yingyue Xin, Xiaoqi Chen, Shinan Wang, Xiang Chen, Jiahao Fan, Chenyu Huang, Xin Xu, Zhoujie Hou, Chen Wei, Quanying Liu

机构 * Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China（南方科技大学生物医学工程系，深圳，中国） ； School of Computer Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China（香港中文大学（深圳）计算机科学与工程学院，深圳，中国） ； Omni-Intelligence, Shenzhen, China（奥米智能，深圳，中国） ； Shenzhen Loop Area Institute, Shenzhen, China（深圳环城研究院，深圳，中国） 纠错

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

AI总结 针对脑电图基础模型评估碎片化问题，提出统一基准OmniEEG-Bench，涵盖六类任务、54个数据集，并揭示预训练数据多样性和模型大小与性能的缩放律关系。

Comments 28 pages, 13 figures, 8 tables; benchmark of EEG foundation models

Dendrite: A Real-Time Python Application for Online Brain-Computer Interface Research and Development

Dendrite：用于在线脑机接口研究与开发的实时Python应用程序

Niko Kroflic, Jan Babič

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

AI总结 研究旨在开发在线脑机接口软件，核心方法是用Python编写Dendrite应用程序，它整合信号采集、解码器训练与实时推理，能同时记录多信号流并并发处理，可重现且开源，为在线BCI范式开发评估提供了系统。

Comments 15 pages, 5 figures

Federated deep transfer learning for EEG decoding using multiple BCI tasks

Xiaoxi Wei, A. Aldo Faisal

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

Comments 4 pages, 3 figures

Overcoming the BCI Calibration Bottleneck: A Clinically-Grounded Architecture using Riemannian Alignment and Stochastic Weight Averaging

克服脑机接口校准瓶颈：一种基于黎曼对齐和随机权重平均的临床基础架构

Immanuvel Prathap Sagayaraju

机构 * University of Bern（伯恩大学） 纠错

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

AI总结 研究针对脑机接口校准瓶颈问题，构建结合逐会话独立成分分析、黎曼欧几里得对齐和随机权重平均稳定EEGNet的深度学习管道，在基准测试和案例研究中取得高准确率，验证了对二元运动想象的硬件无关零样本有效性。

Comments 10 pages, 8 figures

Pseudo-online framework for BCI evaluation: A MOABB perspective

Igor Carrara, Théodore Papadopoulo

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

Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders

Ozan Ozdenizci, Ye Wang, Toshiaki Koike-Akino, Deniz Erdogmus

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

Comments 9th International IEEE EMBS Conference on Neural Engineering (NER'19)

Federated Transfer Learning for EEG Signal Classification

Ce Ju, Dashan Gao, Ravikiran Mane, Ben Tan, Yang Liu, Cuntai Guan

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

Comments 6 pages, 2 figures, Accepted for IEEE Engineering in Medicine and Biology Society (EMBC) 2020 GitHub: https://github.com/DashanGao/Federated-Transfer-Leraning-for-EEG

Journal ref 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Montreal, QC, Canada, 2020, pp. 3040-3045

ChineseEEG-2: An EEG Dataset for Multimodal Semantic Alignment and Neural Decoding during Reading and Listening

Sitong Chen, Beiqianyi Li, Cuilin He, Dongyang Li, Mingyang Wu, Xinke Shen, Song Wang, Xuetao Wei, Xindi Wang, Haiyan Wu, Quanying Liu

专题命中 BCI数据与评测 ：EEG(title,abstract)；neural decoding(title,abstract)；分类 eess.SP

Synthetic Data Generation for Brain-Computer Interfaces: Overview, Benchmarking, and Future Directions

脑机接口中的合成数据生成：概述、基准测试与未来方向

Ziwei Wang, Zhentao He, Xingyi He, Hongbin Wang, Tianwang Jia, Jingwei Luo, Siyang Li, Xiaoqing Chen, Dongrui Wu

机构 * School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China（华中科技大学人工智能与自动化学院，武汉，中国） ； Zhongguancun Academy, Beijing, China（中关村学院，北京，中国） 纠错

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

AI总结 本文综述了用于脑机接口的合成脑数据生成方法，讨论了不同生成方法的分类、基准实验、评估指标和应用，以及未来研究方向，旨在提升数据效率和隐私保护的脑机接口系统。

Comments 33 pages, 8 figures

Online Adaptation via Dual-Stage Alignment and Self-Supervision for Fast-Calibration Brain-Computer Interfaces

Sheng-Bin Duan, Jian-Long Hao, Tian-Yu Xiang, Xiao-Hu Zhou, Mei-Jiang Gui, Xiao-Liang Xie, Shi-Qi Liu, Zeng-Guang Hou

机构 * School of Information, Shanxi University of Finance and Economics（山西财经大学信息学院） ； Chinese Academy of Sciences（中国科学院） ； State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation（多模态人工智能系统国家重点实验室，自动化研究所） ； University of Chinese Academy of Sciences（中国科学院大学） ； School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院） ； CAS Center for Excellence in Brain Science and Intelligence Technology（中国科学院脑科学与智能技术卓越创新中心） ； Joint Laboratory of Intelligence Science and Technology, Institute of Systems Engineering, Macau University of Science and Technology（澳门科技大学智能科学与技术联合实验室） 纠错

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

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification

Ahmed G. Habashi, Ahmed M. Azab, Seif Eldawlatly, Gamal M. Aly

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

Decoding Multi-class Motor-related Intentions with User-optimized and Robust BCI System Based on Multimodal Dataset

Jeong-Hyun Cho, Byoung-Hee Kwon, Byeong-Hoo Lee

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

Comments Submitted to 2023 11th IEEE International Winter Conference on Brain-Computer Interface

Transfer Learning between Motor Imagery Datasets using Deep Learning -- Validation of Framework and Comparison of Datasets

Pierre Guetschel, Michael Tangermann

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

Comments Keywords: EEG, BCI, Motor Imagery, Deep Learning, Transfer Learning, Cross-Dataset. 3 figures, 2 tables

When Brain Foundation Model Meets Cauchy-Schwarz Divergence: A New Framework for Cross-Subject Motor Imagery Decoding

当脑基础模型遇见柯西-施瓦茨散度：一种跨受体运动想象解码的新框架

Jinzhou Wu, Baoping Tang, Qikang Li, Yi Wang, Cheng Li, Shujian Yu

机构 * State Key Laboratory of Mechanical Transmission, College of Mechanical and Vehicle Engineering, Chongqing University（机械传动国家重点实验室，重庆大学） 纠错

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

AI总结 本文提出一种新的多源域适应框架，利用预训练的脑基础模型进行动态源受体选择，并结合柯西-施瓦茨散度实现特征和决策层面对齐，以提高跨受体运动想象解码的准确率。

Comments This work has been submitted to Elsevier for possible publication

AdaBrain-Bench: Benchmarking Brain Foundation Models for Brain-Computer Interface Applications

Jiamin Wu, Zichen Ren, Junyu Wang, Pengyu Zhu, Yonghao Song, Mianxin Liu, Qihao Zheng, Lei Bai, Wanli Ouyang, Chunfeng Song

机构 * Shanghai Artificial Intelligence Laboratory（上海人工智能实验室） ； The Chinese University of Hong Kong（香港中文大学） ； Tsinghua University（清华大学） ； North China Electric Power University（华北电力大学） 纠错

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

Confidence-Aware Subject-to-Subject Transfer Learning for Brain-Computer Interface

Dong-Kyun Han, Serkan Musellim, Dong-Young Kim, Ji-Hoon Jeong

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

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

Evaluating Fast Adaptability of Neural Networks for Brain-Computer Interface

Anupam Sharma, Krishna Miyapuram

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

Comments Accepted in IJCNN 2024

Priming Cross-Session Motor Imagery Classification with A Universal Deep Domain Adaptation Framework

Zhengqing Miao, Xin Zhang, Carlo Menon, Yelong Zheng, Meirong Zhao, Dong Ming

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

Comments 17 pages, 5figures

Impact of dataset size and long-term ECoG-based BCI usage on deep learning decoders performance

Maciej Śliwowski, Matthieu Martin, Antoine Souloumiac, Pierre Blanchart, Tetiana Aksenova

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