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ERD analysis method in motor imagery brain-computer interfaces for accurate switch input

机译:运动图像脑机接口中的ERD分析方法以实现准确的开关输入

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Motor imagery brain-computer interface (MIBCI) can control computers using MI. However, input accuracy is low, partly owing to individual variability in event-related desynchronization (ERD) detection among different subjects. In an earlier study, we determined that using a max power in the mu-band method, i.e., the peak trace method (PTM), is effective for ERD detection. In this study, we compare the PTM to the band power method to determine the most effective method for ERD detection during MI tasks. Experimental results indicate that we could detect ERD using the PTM; however, Mi-state estimation was difficult. We also found that the PTM might be effective for ERD detection in subjects with MI experience.
机译:运动图像脑机接口(MIBCI)可以使用MI控制计算机。但是,输入精度低,部分原因是不同主体之间事件相关的失步(ERD)检测中的个体差异。在较早的研究中,我们确定在mu波段方法中使用最大功率,即峰值跟踪方法(PTM),对于ERD检测是有效的。在这项研究中,我们将PTM与频段功率方法进行比较,以确定在MI任务期间检测ERD的最有效方法。实验结果表明,我们可以使用PTM来检测ERD。但是,Mi-state估计很困难。我们还发现,PTM可能对有MI经验的受试者的ERD检测有效。

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