Motor imagery and mental fatigue: inter-relationship and EEG based estimation

被引：0
作者：
Upasana Talukdar
Shyamanta M. Hazarika
John Q. Gan
机构：
[1] Tezpur University,Biomimetic and Cognitive Robotics Lab, Department of Computer Science and Engineering
[2] Indian Institute of Technology,Mechatronics and Robotics Lab, Department of Mechanical Engineering
[3] University of Essex,School of Computer Science and Electronic Engineering
来源：
Journal of Computational Neuroscience | 2019年 / 46卷
关键词：
Motor imagery; Mental fatigue; Brain Computer Interface; EEG;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
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页码：55 / 76
页数：21
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