运动图像应用的脑电图电极选择方法

M. Riyadi, Oltfaz Rabakhir Rane, Afandi Amir, T. Prakoso, I. Setiawan
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引用次数: 0

摘要

脑机接口(BCI)技术是一种常用的无创描述脑信号活动的技术。用于记录大脑活动的脑电图设备的发展仍在继续,无论是在准确性,适用性,计算和成本方面。然而,复杂性随着电极数量的增加而增加。在一些研究中,最小化电极的数量可以在不影响准确性的情况下减少计算时间、成本和EEG设备的形状。通过选择与活性高度相关的特定电极,可以减少电极的使用。本研究采用相关系数法确定最佳电极对。此外,消除了具有相似特征的电极。实验和测试结果表明,与使用所有电极相比,结果非常好,其中平均精度和F1分数分别提高了2%和4%,增加之后计算时间减少,调试时间平均减少了35%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Method of Electroencephalography Electrode Selection for Motor Imagery Application
Brain-computer interface (BCI) technology is commonly used to describe the brain signal activity non-invasively. The development of EEG devices which is used to record brain activity continues to be carried out, both in terms of accuracy, suitability, computation, and cost. However, the complexity arises with increased electrode numbers. In some studies, minimizing the number of electrodes can be a solution to reduce computational time, cost, and the shape of the EEG device, without compromising the level of accuracy. By choosing particular electrodes which are highly related to the activity, the electrode usage can be reduced. This study used correlation coefficient method which is proposed to determine the best electrode pairs. Moreover, the electrodes which have similar features is eliminated. Based on the experimental and test results, it showed that the results were very good, where the average accuracy and F1 Score was increasing by 2% and 4% compared to the use of all electrodes, this increasing was followed by a decreasing in computation time with an average decreasing in debugging time by 35%.
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