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High Theta and Low Alpha Powers May Be Indicative of BCI-Illiteracy in Motor Imagery

机译:高Theta和低alpha功率可能表示汽车影像中的BCI素养

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摘要

In most brain computer interface (BCI) systems, some target users have significant difficulty in using BCI systems. Such target users are called ‘BCI-illiterate’. This phenomenon has been poorly investigated, and a clear understanding of the BCI-illiteracy mechanism or a solution to this problem has not been reported to date. In this study, we sought to demonstrate the neurophysiological differences between two groups (literate, illiterate) with a total of 52 subjects. We investigated recordings under non-task related state (NTS) which is collected during subject is relaxed with eyes open. We found that high theta and low alpha waves were noticeable in the BCI-illiterate relative to the BCI-literate people. Furthermore, these high theta and low alpha wave patterns were preserved across different mental states, such as NTS, resting before motor imagery (MI), and MI states, even though the spatial distribution of both BCI-illiterate and BCI-literate groups did not differ. From these findings, an effective strategy for pre-screening subjects for BCI illiteracy has been determined, and a performance factor that reflects potential user performance has been proposed using a simple combination of band powers. Our proposed performance factor gave an r = 0.59 (r2 = 0.34) in a correlation analysis with BCI performance and yielded as much as r = 0.70 (r2 = 0.50) when seven outliers were rejected during the evaluation of whole data (N = 61), including BCI competition datasets (N = 9). These findings may be directly applicable to online BCI systems.
机译:在大多数脑计算机接口(BCI)系统中,某些目标用户在使用BCI系统方面存在很大困难。这样的目标用户称为“不识字的BCI”。对此现象的调查不充分,迄今为止,尚未报道过对BCI文盲机制的清晰理解或对该问题的解决方案。在这项研究中,我们试图证明两组(有文化的,文盲的)有52位受试者的神经生理学差异。我们调查了非任务相关状态(NTS)下的记录,这些记录是在受试者睁开眼睛放松时收集的。我们发现相对于BCI识字的人,在BCI文盲中,高theta波和低α波很明显。此外,即使在BCI文盲和BCI文盲组的空间分布没有变化的情况下,这些高theta波和低α波模式也保留在不同的精神状态(例如NTS)中,这些状态处于运动图像(MI)和MI状态之前。不同。根据这些发现,已经确定了一种针对BCI文盲进行预筛查的有效策略,并且已经提出了使用频段功率的简单组合来反映潜在用户性能的性能因素。我们提出的性能因子在与BCI性能的相关性分析中给出了r = 0.59(r 2 = 0.34),收益高达r = 0.70(r 2 = 0.50)在评估包括BCI竞争数据集(N = 9)的整个数据(N = 61)时拒绝了七个异常值。这些发现可能直接适用于在线BCI系统。

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