Wierzgała Piotr, Zapała Dariusz, Wojcik Grzegorz M, Masiak Jolanta
Department of Neuroinformatics, Faculty of Mathematics, Physics and Computer Science, Institute of Computer Science Maria Curie-Sklodowska University, Lublin, Poland.
Department of Experimental Psychology The John Paul II Catholic University of Lublin, Lublin, Poland.
Front Neuroinform. 2018 Nov 6;12:78. doi: 10.3389/fninf.2018.00078. eCollection 2018.
Brain-Computer Interfaces (BCI) constitute an alternative channel of communication between humans and environment. There are a number of different technologies which enable the recording of brain activity. One of these is electroencephalography (EEG). The most common EEG methods include interfaces whose operation is based on changes in the activity of Sensorimotor Rhythms (SMR) during imagery movement, so-called Motor Imagery BCI (MIBCI).The present article is a review of 131 articles published from 1997 to 2017 discussing various procedures of data processing in MIBCI. The experiments described in these publications have been compared in terms of the methods used for data registration and analysis. Some of the studies (76 reports) were subjected to meta-analysis which showed corrected average classification accuracy achieved in these studies at the level of 51.96%, a high degree of heterogeneity of results ( = 1806577.61; = 486; < 0.001; = 99.97%), as well as significant effects of number of channels, number of mental images, and method of spatial filtering. On the other hand the meta-regression failed to provide evidence that there was an increase in the effectiveness of the solutions proposed in the articles published in recent years. The authors have proposed a newly developed standard for presenting results acquired during MIBCI experiments, which is designed to facilitate communication and comparison of essential information regarding the effects observed. Also, based on the findings of descriptive analysis and meta-analysis, the authors formulated recommendations regarding practices applied in research on signal processing in MIBCIs.
脑机接口（BCI）构成了人类与环境之间另一种通信渠道。有多种不同技术可用于记录大脑活动。其中之一是脑电图（EEG）。最常见的EEG方法包括基于想象运动期间感觉运动节律（SMR）活动变化进行操作的接口，即所谓的运动想象脑机接口（MIBCI）。本文是对1997年至2017年发表的131篇文章的综述，这些文章讨论了MIBCI中各种数据处理程序。已根据用于数据记录和分析的方法对这些出版物中描述的实验进行了比较。其中一些研究（76份报告）进行了荟萃分析，结果显示这些研究中校正后的平均分类准确率达到51.96%，结果具有高度异质性（ = 1806577.61； = 486； < 0.001； = 99.97%），以及通道数量、心理图像数量和空间滤波方法的显著影响。另一方面，荟萃回归未能提供证据表明近年来发表的文章中提出的解决方案的有效性有所提高。作者提出了一种新开发的标准，用于呈现MIBCI实验期间获得的结果，该标准旨在促进关于观察到的效果的基本信息的交流和比较。此外，基于描述性分析和荟萃分析的结果，作者针对MIBCIs信号处理研究中应用的实践提出了建议。
