Systematic comparison between a wireless EEG system with dry electrodes and a wired EEG system with wet electrodes.
Systematic comparison between a wireless EEG system with dry electrodes and a wired EEG system with wet electrodes.
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DOI：
10.1016/j.neuroimage.2018.09.012
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发表时间：
2019-01-01
期刊：
影响因子：
5.7
通讯作者：
Knight RT
中科院分区：
文献类型：
--
作者：
Kam JWY;Griffin S;Shen A;Patel S;Hinrichs H;Heinze HJ;Deouell LY;Knight RT
干电极技术的最新进展促进了在以前不可能的情况下记录EEG，这要归功于相对快速的电极制备和避免将凝胶施加到受试者的头发上。然而，要成为真正的替代品，这些系统应与临床或研究应用中常用的最先进的湿EEG系统进行比较。在我们的研究中，我们进行了系统的比较电极应用速度，受试者的舒适度，最关键的电生理信号质量之间的传统和有线Biosemi脑电图系统使用湿主动电极和紧凑型和无线F1脑电图系统组成的干被动电极。所有受试者（n = 27）在不同的日子参加了两个记录会话，一个使用湿EEG系统，一个使用干EEG系统，其中会话顺序在受试者之间平衡。在每个会话中，我们记录了他们的脑电图在不同的休息期间，眼睛打开和关闭，然后是两个版本的一系列视觉呈现目标检测任务。每个任务组件允许反映数据的不同特征的神经测量，包括典型低频带中的频谱功率，事件相关的潜在组件（具体来说，P3 b）和基于机器学习的单次试验分类。这两个系统的性能在大多数指标上都相似，包括P3 b振幅和地形，以及静止时的低频（theta、alpha和beta）谱功率。两种EEG系统在分类分析中的表现都高于偶然性，湿系统相对于干系统具有边际优势。重要的是，所有上述电生理指标显示出两种EEG系统之间的显著正相关性（r = 0.54-0.89）。这众多的措施提供了一个全面的比较，捕捉EEG数据的不同方面，包括时间精度，频域以及活动的多元模式。两者合计，我们的结果表明，在本实验中使用的干EEG系统可以有效地记录在研究和临床环境中常用的电生理测量，其质量与传统的湿EEG系统相当。
Recent advances in dry electrodes technology have facilitated the recording of EEG in situations not previously possible, thanks to the relatively swift electrode preparation and avoidance of applying gel to subject’s hair. However, to become a true alternative, these systems should be compared to state-of-the-art wet EEG systems commonly used in clinical or research applications. In our study, we conducted a systematic comparison of electrodes application speed, subject comfort, and most critically electrophysiological signal quality between the conventional and wired Biosemi EEG system using wet active electrodes and the compact and wireless F1 EEG system consisting of dry passive electrodes. All subjects (n = 27) participated in two recording sessions on separate days, one with the wet EEG system and one with the dry EEG system, in which the session order was counterbalanced across subjects. In each session, we recorded their EEG during separate rest periods with eyes open and closed followed by two versions of a serial visual presentation target detection task. Each task component allows for a neural measure reflecting different characteristics of the data, including spectral power in canonical low frequency bands, event-related potential components (specifically, the P3b), and single trial classification based on machine learning. The performance across the two systems was similar in most measures, including the P3b amplitude and topography, as well as low frequency (theta, alpha, and beta) spectral power at rest. Both EEG systems performed well above chance in the classification analysis, with a marginal advantage of the wet system over the dry. Critically, all aforementioned electrophysiological metrics showed significant positive correlations (r = 0.54–0.89) between the two EEG systems. This multitude of measures provides a comprehensive comparison that captures different aspects of EEG data, including temporal precision, frequency domain as well as multivariate patterns of activity. Taken together, our results indicate that the dry EEG system used in this experiment can effectively record electrophysiological measures commonly used across the research and clinical contexts with comparable quality to the conventional wet EEG system.
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DOI：
10.3390/s140712847
发表时间：
2014-07-18
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Lopez-Gordo MA;Sanchez-Morillo D;Pelayo Valle F
通讯作者：
Pelayo Valle F
影响因子：
4
作者：
De Vos, Maarten;Kroesen, Markus;Debener, Stefan
通讯作者：
Debener, Stefan
影响因子：
--
作者：
Pinho, Francisco;Cerqueira, Joao;Dias, Nuno
通讯作者：
Dias, Nuno
影响因子：
--
作者：
Oostenveld R;Fries P;Maris E;Schoffelen JM
通讯作者：
Schoffelen JM
影响因子：
4.6
作者：
Debener S;Emkes R;De Vos M;Bleichner M
通讯作者：
Bleichner M