Even though it has long been felt that psychological state influences the performance of brain-computer interfaces (BCI), formal analysis to support this hypothesis has been scant. This study investigates the inter-relationship between motor imagery (MI) and mental fatigue using EEG: a. whether prolonged sequences of MI produce mental fatigue and b. whether mental fatigue affects MI EEG class separability. Eleven participants participated in the MI experiment, 5 of which quit in the middle because of experiencing high fatigue. The growth of fatigue was monitored using the Kernel Partial Least Square (KPLS) algorithm on the remaining 6 participants which shows that MI induces substantial mental fatigue. Statistical analysis of the effect of fatigue on motor imagery performance shows that high fatigue level significantly decreases MI EEG separability. Collectively, these results portray an MI-fatigue inter-connection, emphasizing the necessity of developing adaptive MI BCI by tracking mental fatigue.

中文翻译：

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运动图像和精神疲劳：相互关系和基于EEG的估计。

尽管长期以来人们一直认为心理状态会影响脑机接口（BCI）的性能，但仍缺乏形式化的分析来支持这一假设。本研究使用脑电图研究运动图像（MI）与精神疲劳之间的相互关系：长时间的MI发作是否会导致精神疲劳和b。精神疲劳是否会影响MI EEG类的可分离性。11名参与者参加了MI实验，其中5名由于经历高疲劳而中途退出。使用内核偏最小二乘（KPL）算法对其余6位参与者进行了疲劳监测，这表明MI引起了严重的精神疲劳。疲劳对运动图像性能影响的统计分析表明，高疲劳水平会显着降低MI EEG的可分离性。这些结果共同说明了MI疲劳的相互联系，强调了通过跟踪精神疲劳来发展适应性MI BCI的必要性。