Brain-Computer Interfaces最新文献

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Impact of age, VR, immersion, and spatial resolution on classifier performance for a MI-based BCI 年龄，VR，沉浸和空间分辨率对基于mi的BCI分类器性能的影响

IF 2.1 Q2 Engineering

Brain-Computer Interfaces

Pub Date : 2022-04-04 DOI: 10.1080/2326263x.2022.2054606

D. A. Blanco-Mora, A. Aldridge, C. Jorge, A. Vourvopoulos, P. Figueiredo, S., Bermúdez I Badia

There are many factors outlined in the signal processing pipeline that impact brain–computer interface (BCI) performance, but some methodological factors do not depend on signal processing. Nevertheless, there is a lack of research assessing the effect of such factors. Here, we investigate the impact of VR, immersiveness, age, and spatial resolution on the classifier performance of a Motor Imagery (MI) electroencephalography (EEG)-based BCI in naïve participants. We found significantly better performance for VR compared to non-VR (15 electrodes: VR 77.48 ± 6.09%, non-VR 73.5 ± 5.89%, p = 0.0096; 12 electrodes: VR 73.26 ± 5.2%, non-VR 70.87 ± 4.96%, p = 0.0129; 7 electrodes: VR 66.74 ± 5.92%, non-VR 63.09 ± 8.16%, p = 0.0362) and better performance for higher electrode quantity, but no significant differences were found between immersive and non-immersive VR. Finally, there was not a statistically significant correlation found between age and classifier performance, but there was a direct relation found between spatial resolution (electrode quantity) and classifier performance (r = 1, p = 0.0129, VR; r = 0.99, p = 0.0859, non-VR).

在影响脑机接口(BCI)性能的信号处理管道中列出了许多因素，但一些方法因素并不依赖于信号处理。然而，缺乏评估这些因素影响的研究。在这里，我们研究了VR、沉浸感、年龄和空间分辨率对naïve参与者基于运动图像(MI)脑电图(EEG)的脑机接口分类器性能的影响。我们发现，与非VR相比，VR的性能明显更好(15个电极:VR 77.48±6.09%，非VR 73.5±5.89%，p = 0.0096;12个电极:VR 73.26±5.2%，非VR 70.87±4.96%，p = 0.0129;7种电极:VR 66.74±5.92%，非VR 63.09±8.16%，p = 0.0362)且电极数量越多，效果越好，但沉浸式与非沉浸式VR无显著差异。最后，年龄与分类器性能之间没有统计学意义上的相关性，但空间分辨率(电极数量)与分类器性能之间存在直接关系(r = 1, p = 0.0129, VR;r = 0.99, p = 0.0859，非vr)。

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引用次数: 6

Novel frequency-based approach for detection of steady-state visual evoked potentials for realization of practical brain computer interfaces 基于频率的稳态视觉诱发电位检测新方法，实现实用的脑机接口

IF 2.1 Q2 Engineering

Brain-Computer Interfaces

Pub Date : 2022-03-13 DOI: 10.1080/2326263x.2022.2050513

Mehrnoosh Neghabi, H. Marateb, A. Mahnam

引用次数: 1

Two sides of the same coin: adaptation of BCIs to internal states with user-centered design and electrophysiological features 同一枚硬币的两面:以用户为中心的设计和电生理特征使bci适应内部状态

IF 2.1 Q2 Engineering

Brain-Computer Interfaces

Pub Date : 2022-03-02 DOI: 10.1080/2326263x.2022.2041294

Yiyuan Han, P. Ziebell, A. Riccio, S. Halder

The ideal brain–computer interface (BCI) adapts to the user’s state to enable optimal BCI performance. Two methods of BCI adaptation are commonly applied: User-centered design (UCD) responds to individual user needs and requirements. Passive BCIs can adapt via online analysis of electrophysiological signals. Despite similar goals, these methods are rarely discussed in combi-nation. Hence, we organized a workshop for the 8th International BCI Meeting 2021 to discuss the combined application of both methods. Here we expand upon the workshop by discussing UCD in more detail regarding its utility for end-users as well as non-end-user-based early-stage BCI development. Furthermore, we explore electrophysiology-based online user state adaptation concerning consciousness and pain detection. The integration of the numerous BCI user state adaptation methods into a unified process remains challenging. Yet, further systematic accumula- tion of specific knowledge about assessment and integration of internal user states bears great potential for BCI optimization.

理想的脑机接口(BCI)能够适应用户的状态，从而实现最佳的BCI性能。BCI适应的常用方法有两种:以用户为中心的设计(user -centered design, UCD)响应个人用户的需求和要求。被动脑机接口可以通过在线分析电生理信号来适应。尽管目标相似，但很少将这些方法结合起来讨论。因此，我们为2021年第八届国际脑机接口会议组织了一个研讨会，讨论两种方法的结合应用。在这里，我们通过更详细地讨论UCD对最终用户以及非基于最终用户的早期BCI开发的效用来扩展研讨会。此外，我们探索基于电生理学的在线用户状态适应，涉及意识和疼痛检测。将众多BCI用户状态适应方法集成到一个统一的过程中仍然具有挑战性。然而，进一步系统地积累有关内部用户状态评估和集成的具体知识，对BCI优化具有很大的潜力。

引用次数: 7

When should MI-BCI feature optimization include prior knowledge, and which one? 什么时候MI-BCI特征优化应该包括先验知识，哪一个?

IF 2.1 Q2 Engineering

Brain-Computer Interfaces

Pub Date : 2022-02-14 DOI: 10.1080/2326263x.2022.2033073

Camille Benaroch, M. Yamamoto, A. Roc, Pauline Dreyer, C. Jeunet, F. Lotte

引用次数: 6

Coherence-based connectivity analysis of EEG and EMG signals during reach-to-grasp movement involving two weights 基于相干性的两权手抓动作脑电和肌电信号连通性分析

IF 2.1 Q2 Engineering

Brain-Computer Interfaces

Pub Date : 2022-02-12 DOI: 10.1080/2326263x.2022.2029308

C. D. Guerrero-Méndez, A. F. Ruiz-Olaya

引用次数: 5

The 8^th international brain-computer interface meeting, BCIs: the next frontier. 第八届国际脑机接口会议，BCIs：下一个前沿。

IF 1.8 Q3 ENGINEERING, BIOMEDICAL

Brain-Computer Interfaces

Pub Date : 2022-01-01 Epub Date: 2022-05-10 DOI: 10.1080/2326263x.2022.2066853

Jennifer L Collinger, Dean J Krusienski

引用次数: 0

Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier. 第八届国际脑机接口会议研讨会：BCIs：下一个前沿。

IF 1.8 Q3 ENGINEERING, BIOMEDICAL

Brain-Computer Interfaces

Pub Date : 2022-01-01 Epub Date: 2022-02-08 DOI: 10.1080/2326263X.2021.2009654

Jane E Huggins, Dean Krusienski, Mariska J Vansteensel, Davide Valeriani, Antonia Thelen, Sergey Stavisky, James J S Norton, Anton Nijholt, Gernot Müller-Putz, Nataliya Kosmyna, Louis Korczowski, Christoph Kapeller, Christian Herff, Sebastian Halder, Christoph Guger, Moritz Grosse-Wentrup, Robert Gaunt, Aliceson Nicole Dusang, Pierre Clisson, Ricardo Chavarriaga, Charles W Anderson, Brendan Z Allison, Tetiana Aksenova, Erik Aarnoutse

The Eighth International Brain-Computer Interface (BCI) Meeting was held June 7-9th, 2021 in a virtual format. The conference continued the BCI Meeting series' interactive nature with 21 workshops covering topics in BCI (also called brain-machine interface) research. As in the past, workshops covered the breadth of topics in BCI. Some workshops provided detailed examinations of specific methods, hardware, or processes. Others focused on specific BCI applications or user groups. Several workshops continued consensus building efforts designed to create BCI standards and increase the ease of comparisons between studies and the potential for meta-analysis and large multi-site clinical trials. Ethical and translational considerations were both the primary topic for some workshops or an important secondary consideration for others. The range of BCI applications continues to expand, with more workshops focusing on approaches that can extend beyond the needs of those with physical impairments. This paper summarizes each workshop, provides background information and references for further study, presents an overview of the discussion topics, and describes the conclusion, challenges, or initiatives that resulted from the interactions and discussion at the workshop.

第八届国际脑机接口（BCI）会议于 2021 年 6 月 7 日至 9 日以虚拟形式举行。会议延续了BCI会议系列的互动性质，21个研讨会涵盖了BCI（也称脑机接口）研究的各个主题。与以往一样，研讨会涵盖了 BCI 领域的广泛主题。一些研讨会对特定方法、硬件或流程进行了详细研究。其他研讨会则侧重于特定的生物介入应用或用户群体。一些研讨会继续努力达成共识，旨在建立生物识别（BCI）标准，增加研究间比较的便利性，提高荟萃分析和大型多站点临床试验的潜力。伦理和转化方面的考虑既是一些研讨会的主要议题，也是其他研讨会的重要次要考虑因素。BCI的应用范围在不断扩大，越来越多的研讨会将重点放在可以超越肢体障碍者需求的方法上。本文对每场研讨会进行了总结，提供了背景信息和进一步研究的参考资料，概述了讨论主题，并介绍了研讨会上的互动和讨论所产生的结论、挑战或倡议。

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引用次数: 0

Extending Brain-Computer Interface Access with a Multilingual Language Model in the P300 Speller. 用P300拼写器中的多语言模型扩展脑机接口访问。

IF 2.1 Q2 Engineering

Brain-Computer Interfaces

Pub Date : 2022-01-01 DOI: 10.1080/2326263x.2021.1993426

P Loizidou, E Rios, A Marttini, O Keluo-Udeke, J Soetedjo, J Belay, K Perifanos, N Pouratian, W Speier

Brain-computer interfaces (BCI) such as the P300 speller have the potential to restore communication to advanced-stage neuromuscular disease patients. Research has improved typing speed and accuracy through innovations including the use of language models. While significant advances have been made, implementations have largely been restricted to a single language, primarily English. It is unclear whether these improvements would extend to other languages that present potential technical hurdles due to different alphabets and grammatical structures. Here, we adapt a language model-based classifier designed for English to two other languages, Spanish and Greek, to demonstrate the generalizability of these methods. Online experimental trials with 30 healthy native English, Spanish, and Greek speakers showed no significant difference between performances using the different versions of the system (66.20 vs. 61.97 vs. 60.89 bits/minute). Extending these methods across languages allows for expanding access to BCI systems to other populations, particularly in the developing world.

像P300拼写器这样的脑机接口(BCI)有可能恢复晚期神经肌肉疾病患者的交流。研究人员通过使用语言模型等创新手段提高了打字速度和准确性。虽然取得了重大进展，但实现在很大程度上仅限于一种语言，主要是英语。目前尚不清楚这些改进是否会扩展到其他语言，这些语言由于不同的字母和语法结构而存在潜在的技术障碍。在这里，我们将为英语设计的基于语言模型的分类器应用于其他两种语言，西班牙语和希腊语，以证明这些方法的泛化性。对30名健康的母语为英语、西班牙语和希腊语的人进行的在线实验表明，使用不同版本系统的表现之间没有显著差异(66.20比特/分钟、61.97比特/分钟和60.89比特/分钟)。跨语言扩展这些方法可以将BCI系统扩展到其他人群，特别是发展中国家的人群。

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引用次数: 2

Improving longitudinal P300-BCI performance for people with ALS using a data augmentation and jitter correction approach 使用数据增强和抖动校正方法改善ALS患者的纵向P300-BCI性能

IF 2.1 Q2 Engineering

Brain-Computer Interfaces

Pub Date : 2021-12-23 DOI: 10.1080/2326263x.2021.2014678

A. H. Zisk, S. B. Borgheai, J. McLinden, R. J. Deligani, Y. Shahriari

引用次数: 1

High-wearable EEG-based transducer for engagement detection in pediatric rehabilitation 基于脑电图的高可穿戴传感器在儿童康复中的参与检测

IF 2.1 Q2 Engineering

Brain-Computer Interfaces

Pub Date : 2021-12-16 DOI: 10.1080/2326263x.2021.2015149

Andrea Apicella, P. Arpaia, Salvatore Giugliano, Giovanna Mastrati, N. Moccaldi

引用次数: 2

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