Bevilacqua Michele, Perdikis Serafeim, Millan Jose Del R
1 Defitech Chair of Clinical NeuroengineeringCenter for Neuroprosthetics and Brain Mind Institute, EPFL CH-1202 Geneva Switzerland.
2 Brain-Computer Interfaces and Neural Engineering Laboratory, School of Computer Science and Electronic EngineeringUniversity of Essex Colchester CO4 3SQ U.K.
IEEE Open J Eng Med Biol. 2020 Feb 14;1:17-22. doi: 10.1109/OJEMB.2019.2962879. eCollection 2020.
Brain-computer interface (BCI) spelling is a promising communication solution for people in paralysis. Currently, BCIs suffer from imperfect decoding accuracy which calls for methods to handle spelling mistakes. Detecting error-related potentials (ErrPs) has been early identified as a potential remedy. Nevertheless, few works have studied the elicitation of ErrPs during engagement with other BCI tasks, especially when BCI feedback is provided continuously. Here, we test the possibility of correcting errors during pseudo-online Motor Imagery (MI) BCI spelling through ErrPs, and investigate whether BCI feedback hinders their generation. Ten subjects performed a series of MI spelling tasks with and without observing BCI feedback. The average pseudo-online ErrP detection accuracy was found to be significantly above the chance level in both conditions and did not significantly differ between the two (74% with, and 78% without feedback). Our results support the possibility to detect ErrPs during MI-BCI spelling and suggest the absence of any BCI feedback-related interference.
脑机接口（BCI）拼写对于瘫痪患者来说是一种很有前景的交流解决方案。目前，BCI存在解码准确率不完善的问题，这就需要有处理拼写错误的方法。检测错误相关电位（ErrP）早就被确定为一种潜在的补救措施。然而，很少有研究探讨在参与其他BCI任务过程中ErrP的诱发情况，尤其是在持续提供BCI反馈的时候。在此，我们测试了通过ErrP在伪在线运动想象（MI）BCI拼写过程中纠正错误的可能性，并研究BCI反馈是否会阻碍其产生。十名受试者进行了一系列有或没有观察BCI反馈的MI拼写任务。发现在两种情况下，平均伪在线ErrP检测准确率均显著高于随机水平，且两者之间没有显著差异（有反馈时为74%，无反馈时为78%）。我们的结果支持在MI-BCI拼写过程中检测ErrP的可能性，并表明不存在任何与BCI反馈相关的干扰。
