Neo Phoebe S-H, Mayne Terence, Fu Xiping, Huang Zhiyi, Franz Elizabeth A
Department of Computer Science, University of Otago, Dunedin, New Zealand.
Department of Psychology, University of Otago, Dunedin, New Zealand.
Health Inf Sci Syst. 2021 Mar 13;9(1):13. doi: 10.1007/s13755-021-00142-y. eCollection 2021 Dec.
Brain-computer interfaces (BCIs) target specific brain activity for neuropsychological rehabilitation, and also allow patients with motor disabilities to control mobility and communication devices. Motor imagery of single-handed actions is used in BCIs but many users cannot control the BCIs effectively, limiting applications in the health systems. Crosstalk is unintended brain activations that interfere with bimanual actions and could also occur during motor imagery. To test if crosstalk impaired BCI user performance, we recorded EEG in 46 participants while they imagined movements in four experimental conditions using motor imagery: left hand (L), right hand (R), tongue (T) and feet (F). Pairwise classification accuracies of the tasks were compared (LR, LF, LT, RF, RT, FT), using common spatio-spectral filters and linear discriminant analysis. We hypothesized that LR classification accuracy would be lower than every other combination that included a hand imagery due to crosstalk. As predicted, classification accuracy for LR (58%) was reliably the lowest. Interestingly, participants who showed poor LR classification also demonstrated at least one good TR, TL, FR or FL classification; and good LR classification was detected in 16% of the participants. For the first time, we showed that crosstalk occurred in motor imagery, and affected BCI performance negatively. Such effects are effector-sensitive regardless of the BCI methods used; and likely not apparent to the user or the BCI developer. This means that tasks choice is crucial when designing BCI. Critically, the effects of crosstalk appear mitigatable. We conclude that understanding crosstalk mitigation is important for improving BCI applicability.
The online version of this article contains supplementary material available (10.1007/s13755-021-00142-y).
脑机接口（BCIs）旨在针对特定脑活动进行神经心理康复，还能让运动功能障碍患者控制移动和通信设备。BCIs中使用了单手动作的运动想象，但许多用户无法有效控制BCIs，限制了其在医疗系统中的应用。串扰是干扰双手动作的意外脑激活，在运动想象过程中也可能发生。为了测试串扰是否会损害BCI用户的表现，我们在46名参与者想象四种实验条件下的动作时记录了脑电图，这四种实验条件分别是使用运动想象的左手（L）、右手（R）、舌头（T）和脚（F）。使用常见的时空谱滤波器和线性判别分析比较了任务的两两分类准确率（LR、LF、LT、RF、RT、FT）。我们假设由于串扰，LR分类准确率会低于其他包含手部想象的组合。正如预期的那样，LR的分类准确率（58%）确实是最低的。有趣的是，LR分类表现不佳的参与者至少在TR、TL、FR或FL分类中有一项表现良好；16%的参与者LR分类良好。我们首次表明，串扰在运动想象中会发生，并对BCI性能产生负面影响。无论使用何种BCI方法，这种影响对效应器都是敏感的；用户或BCI开发者可能并不明显。这意味着在设计BCI时任务选择至关重要。至关重要的是，串扰的影响似乎是可以减轻的。我们得出结论，了解串扰减轻对于提高BCI的适用性很重要。
本文的在线版本包含补充材料（10.1007/s13755-021-00142-y）。
