脑机接口 / BCI

Bio-inspired Filter Banks for Frequency Recognition of SSVEP-based Brain-computer Interfaces

Ali Fatih Demir, Hüseyin Arslan, Ismail Uysal

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

Comments 9 pages, 8 figures, 5 tables, accepted version

Journal ref IEEE Access, Nov. 2019

Brain Invaders Adaptive versus Non-Adaptive P300 Brain-Computer Interface dataset

Erwan Vaineau, Alexandre Barachant, Anton Andreev, Pedro C. Rodrigues, Grégoire Cattan, Marco Congedo

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

Engagement Estimation in Advertisement Videos with EEG

Sangeetha Balasubramanian, Shruti Shriya Gullapuram, Abhinav Shukla

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

The Shift in brain-state induced by tDCS: an EEG study

Milena Cukic, Miodrag Stokic, Slavoljub Radenkovic, Milos Ljubisavljevic, Dragoljub Donald Pokrajac

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

Comments 23 pages, 6 figures

Real-Time Sleep Staging using Deep Learning on a Smartphone for a Wearable EEG

Abhay Koushik, Judith Amores, Pattie Maes

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

Comments Machine Learning for Health (ML4H) Workshop at NeurIPS 2018 arXiv:1811.07216

Harnessing functional segregation across brain rhythms as a means to detect EEG oscillatory multiplexing during music listening

Dimitrios A. Adamos, Nikolaos Laskaris, Sifis Micheloyannis

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

Comments Pre-print version of the paper published in Journal of Neural Engineering (2018)

EEG source imaging assists decoding in a face recognition task

Rasmus S. Andersen, Anders U. Eliasen, Nicolai Pedersen, Michael Riis Andersen, Sofie Therese Hansen, Lars Kai Hansen

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

Brain-Swarm Interface (BSI): Controlling a Swarm of Robots with Brain and Eye Signals from an EEG Headset

Aamodh Suresh, Mac Schwager

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

A New Statistical Model of Electroencephalogram Noise Spectra for Real-time Brain-Computer Interfaces

Alan Paris, George Atia, Azadeh Vosoughi, Stephen Berman

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

Comments Revised submission to IEEE EMBS Trans. Biomed. Eng. 12 pages, 9 figures

Visual Motion Onset Brain-computer Interface

Jair Pereira Junior, Caio Teixeira, Tomasz M. Rutkowski

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

Comments 10 pages, 5 figures, submitted to a journal MDPI Computers. arXiv admin note: text overlap with arXiv:1506.04458

Identification of interictal epileptic networks from dense-EEG

Mahmoud Hassan, Isabelle Merlet, Ahmad Mheich, Aya Kabbara, Arnaud Biraben, Anca Nica, Fabrice Wendling

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

Comments 30 pages, 5 figures

Detecting single-trial EEG evoked potential using a wavelet domain linear mixed model: application to error potentials classification

J Spinnato, M-C Roubaud, B Burle, B Torrésani

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

Journal ref Journal of Neural Engineering, Institute of Physics: Hybrid Open Access, 2015, 12, pp.036013

Cluster structure of functional networks estimated from high-resolution EEG data

Roberta Sinatra, Fabrizio De Vico Fallani, Laura Astolfi, Fabio Babiloni, Febo Cincotti, Vito Latora, Donatella Mattia

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

Comments 21 pages, 4 figures

Spatial Auditory Brain-computer Interface using Head Related Impulse Response

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

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

Comments 2 pages, 1 figure, accepted for 10th AEARU Workshop on Computer Science and Web Technology February 25-27, 2015, University of Tsukuba, Japan

Bayesian Group Nonnegative Matrix Factorization for EEG Analysis

Bonggun Shin, Alice Oh

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

Defecting or not defecting: how to "read" human behavior during cooperative games by EEG measurements

F. De Vico Fallani, V. Nicosia, R. Sinatra, L. Astolfi, F. Cincotti, D. Mattia, C. Wilke, A. Doud, V. Latora, B. He, F. Babiloni

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

Journal ref PLoS ONE 5(12): e14187 (2010)

Neocortical Dynamics at Multiple Scales: EEG Standing Waves, Statistical Mechanics, and Physical Analogs

Lester Ingber, Paul L. Nunez

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

Fourier Uniformity: An Useful Tool for Analyzing EEG Signals with An Application to Source Localization

Kaushik Majumdar

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

Comments Accepted for oral presententation in the International Joint Conference of Neural Networks 2009, Atlanta, USA. It will not be included in the proceedings for the author's inability to attend the conference

Comparative Analysis of Deep Learning Approaches for Harmful Brain Activity Detection Using EEG

Shivraj Singh Bhatti, Aryan Yadav, Mitali Monga, Neeraj Kumar

机构 * Department of Computer Science and Engineering（计算机科学与工程系） ； Thapar Institute of Engineering and Technology（泰帕尔工程与技术学院） 纠错

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

Comments 6 pages, 5 figures. Presented at IEEE CICT 2024. The paper discusses the application of multimodal data and training strategies in EEG-based brain activity classification

Journal ref 2024 IEEE 8th Int. Conf. on Info. and Comm. Tech. (CICT), pp. 1-6

Subject Adaptive EEG-based Visual Recognition

Pilhyeon Lee, Sunhee Hwang, Seogkyu Jeon, Hyeran Byun

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

Comments Accepted by ACPR 2021. Code is available at https://github.com/DeepBCI/Deep-BCI

Recurrent Neural Networks for P300-based BCI

Ori Tal, Doron Friedman

专题命中 EEG解码 ：BCI(title,journal_ref)；brain-computer interface(abstract)；EEG(abstract)

Journal ref Int'l BCI Conf Graz, Austria, 2017

NeuroStrata: An Electroencephalographic Connectivity-Aware Deep Representation Learning Framework for Dynamic Brain Network Analysis of Mental Stress

NeuroStrata：用于精神压力动态脑网络分析的脑电连接感知深度表示学习框架

Sayantan Acharya, Hamzeh Asgharnezhad, Abbas Khosravi, Douglas Creighton, Roohallah Alizadehsani, U Rajendra Acharya

机构 * Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University（迪肯大学智能系统研究与创新研究所） ； Centre for Health Research, University of Southern Queensland（南昆士兰大学健康研究中心） ； School of Science, Engineering and Digital Technologies, University of Southern Queensland（南昆士兰大学科学、工程与数字技术学院） 纠错

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

AI总结 本研究提出NeuroStrata框架，结合时变有效连接建模与深度表示学习，利用EEG信号分析精神压力，β波段连接准确率达97.3%，为该领域提供可解释自动化方法。

Comments 23 pages, 10 figures, Manuscript currently under review at Engineering Applications of Artificial Intelligence

Modeling and Interpreting Correlations, Null Distributions and Significance Levels in Neural Tracking of Natural Stimuli

自然刺激神经追踪中的相关性、零分布与显著性水平的建模与解释

Simon Geirnaert, Alexander Bertrand, Tom Francart, Jonas Vanthornhout

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

AI总结 本研究针对自然刺激神经追踪的相关性解释问题，提出刺激-响应错位的零假设选择，构建半参数模型生成零归一化追踪分数，通过EEG数据反转原始相关性结论，提供了高效的神经追踪分析方法论。

Rethinking PPG-based Sleep Staging: Datasets, Metrics, and Benchmarks

重新思考基于光体积描记（PPG）的睡眠分期：数据集、指标与基准

Shuntian Zheng, Jiawei Wang, Cong Fu, Huan Yu, Chen Chen, Yu Guan, Sai Gu

机构 * The University of Warwick（华威大学） ； Huashan Hospital, Fudan University（复旦大学附属华山医院） ； Human Phenome Institute, Fudan University（复旦大学人类表型组研究院） 纠错

专题命中 EEG解码 ：EEG(summary_cn,abstract)；分类 cs.LG、cs.HC

AI总结 该研究针对基于PPG的睡眠分期与EEG方法存在的显著差距，开发隐半马尔可夫模型的标签扩展流程，用秒级监督在MESA数据集上提升四类分期准确率3.7-5.7个百分点，且在CFS上零样本迁移有效。

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation

基于计算机视觉的神经学脑电活动抑制架构与实现

Zag ElSayed, Nathan Suer, Grace Westerkamp, Jack Yanchen Liu, Makoto Miyakoshi, Craig Erickson, Ernest Pedapati

机构 * Member, IEEE（IEEE成员） 纠错

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

AI总结 研究针对EEG在认知发展研究中的挑战，引入基于计算机视觉的自动化ICA拒绝标记工具，兼容常用软件接口，通过自动化人工任务，大幅减少处理时间，提高准确率，加速大规模EEG研究及脑电活动抑制任务应用。

Comments 7 pages, 10 figures, Conference

Journal ref ICMLA 2024

AnySleep: a channel-agnostic deep learning system for high-resolution sleep staging in multi-center cohorts

AnySleep：用于多中心队列中高分辨率睡眠分期的通道无关深度学习系统

Niklas Grieger, Jannik Raskob, Siamak Mehrkanoon, Stephan Bialonski

机构 * Department of Medical Engineering and Technomathematics, FH Aachen University of Applied Sciences（医学工程与技术学系，亚琛应用科学大学） ； Department of Information and Computing Sciences, Utrecht University（信息与计算科学系，乌得勒支大学） ； Institute for Data-Driven Technologies, FH Aachen University of Applied Sciences（数据驱动技术研究所，亚琛应用科学大学） 纠错

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

AI总结 研究针对多中心睡眠分期难题，提出AnySleep深度学习系统，能从EEG或EOG数据以可调分辨率评分。经多数据集训练验证，性能达最优，可捕捉短清醒侵入，改善病理状况预测，公开模型助力睡眠研究与生物标志物发现。

Comments 29 pages, 10 figures, 7 tables

Efficient Unsupervised Domain Adaptation Regression for Spatial-Temporal Sensor Fusion

高效无监督领域适应回归用于空间-时间传感器融合

Keivan Faghih Niresi, Ismail Nejjar, Olga Fink

机构 * Intelligent Maintenance and Operations Systems Laboratory, EPFL（智能维护与操作系统实验室，瑞士联邦理工学院） 纠错

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

AI总结 本文提出一种针对回归任务的高效无监督领域适应方法，通过整合空间-时间图神经网络和源目标域扰动逆Gram矩阵对齐，实现无标注数据下的可扩展领域适应，验证于空气质量监测和EEG信号重建任务，取得最佳性能。

Comments Accepted to IEEE Internet of Things Journal

CLSP-REQA: A Real-Time Quality-Aware Closed-Loop Seizure Prediction Framework with Mamba-BiLSTM and Confidence-Gated Intervention

CLSP-REQA：基于Mamba-BiLSTM和置信门控干预的实时质量感知闭环癫痫发作预测框架

Mufeng Chen, Qi Wu, Bingchao Huang, Xiwen Lai, Zekai Chen, Xinge Ouyang, Quansheng Ren

机构 * Department of Engineering Science, University of Oxford（牛津大学工程科学系） ； Mathematical Institute, University of Oxford（牛津大学数学研究所） ； School of Computer Science and Engineering, Beihang University（北航计算机科学与工程学院） ； Aerospace Information Research Institute, Chinese Academy of Sciences（中国科学院航天信息研究所） ； Department of Mechanical Engineering, The University of British Columbia（不列颠哥伦比亚大学机械工程系） ； College of Life Sciences, Hunan Normal University（湖南师范大学生命科学学院） ； School of Electronics, Peking University（北京大学电子学院） 纠错

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

AI总结 提出CLSP-REQA框架，通过嵌入实时EEG质量评估模块和Mamba-BiLSTM骨干网络，结合分层非线性融合函数，在严格跨患者评估下实现优于现有方法的癫痫发作预测性能。

Comments 27 pages, 8 figures, submitted to Biomedical Signal Processing and Control

A comprehensive evaluation of pretraining strategies for channel-agnostic contrastive self-supervision of biosignals

生物信号通道无关对比自监督预训练策略的综合评估

Thea Brüsch, Mikkel N. Schmidt, Tommy S. Alstrøm

机构 * Department of Applied Mathematics and Computer Science（应用数学和计算机科学系） 纠错

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

AI总结 针对生物信号通道可变性问题，提出对比随机导联编码（CRLC）方法，通过随机选择输入通道子集创建正对，在EEG和ECG数据上预训练并微调，在通道无关设置下优于现有策略，并达到与最先进参考模型相当的性能。

NeuralBench: A Unifying Framework to Benchmark NeuroAI Models

NeuralBench：一个统一的神经AI模型评估框架

Hubert Banville, Stéphane d'Ascoli, Simon Dahan, Jérémy Rapin, Marlène Careil, Yohann Benchetrit, Jarod Lévy, Saarang Panchavati, Antoine Ratouchniak, Mingfang, Zhang, Elisa Cascardi, Katelyn Begany, Teon Brooks, Jean-Rémi King

机构 * Brain \& AI team, Meta FAIR ； École Normale Supérieure, Université PSL, CNRS ； Hospital Foundation Adolphe de Rothschild ； MIND, Inria 纠错

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

AI总结 本文提出NeuralBench框架，用于评估神经活动AI模型，包含36个EEG任务和14种深度学习架构，揭示基础模型仅小幅优于任务专用模型，且许多任务仍极具挑战性。

Comments 31 pages, 9 figures