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A systematic review on hybrid EEG/fNIRS in brain-computer interface

机译:脑电电脑界面中混合EEG / FNIR的系统综述

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摘要

As a relatively new field of neurology and computer science, brain computer interface (BCI) has many established and burgeoning applications across scientific disciplines. Many neural monitoring technologies have been developed for BCI studies. Combining multiple monitoring technologies provides a new approach that synthesizes the advantages and overcomes the limitations of each technology. This article presents a systematic review on the applications, limitations, and future directions for the hybridization of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) into one synchronous multimodality. This review investigated research questions on design and usability of hybrid EEG-fNIRS studies. In this article, 765 papers were included in the initial search and 128 papers were selected through the PRISMA protocol. The review results show the possibility of improving the performance of hybrid EEG-fNIRS by optimizing the feature extraction algorithms and physical designing as well as expending more possible applications in information processing related fields.
机译:作为一种相对较新的神经病学和计算机科学领域,脑电脑界面(BCI)在科学学科中有许多建立和蓬勃发展的应用。为BCI研究开发了许多神经监测技术。组合多个监控技术提供了一种新方法,综合了优势并克服了各技术的局限性。本文对脑电图(EEG)和功能近红外光谱(FNIR)杂交的应用,限制和未来方向进行了系统审查,并将近红外光谱(FNIR)分为一个同步多模。本综述关于混合eEG-FNIRS研究的设计和可用性的研究问题。在本文中,765篇论文包含在初始搜索中,通过PRISMA方案选择128篇论文。审查结果表明,通过优化特征提取算法和物理设计以及在信息处理相关字段中消耗更可能的应用程序来提高混合eEG-FNIR的性能的可能性。

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