Zuo Cili, Mao Ying, Liu Qianqian, Wang Xingyu, Jin Jing
Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, P.R. China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Jun 25;38(3):417-424. doi: 10.7507/1001-5515.202010031.
The traditional paradigm of motor-imagery-based brain-computer interface (BCI) is abstract, which cannot effectively guide users to modulate brain activity, thus limiting the activation degree of the sensorimotor cortex. It was found that the motor imagery task of Chinese characters writing was better accepted by users and helped guide them to modulate their sensorimotor rhythms. However, different Chinese characters have different writing complexity (number of strokes), and the effect of motor imagery tasks of Chinese characters with different writing complexity on the performance of motor-imagery-based BCI is still unclear. In this paper, a total of 12 healthy subjects were recruited for studying the effects of motor imagery tasks of Chinese characters with two different writing complexity (5 and 10 strokes) on the performance of motor-imagery-based BCI. The experimental results showed that, compared with Chinese characters with 5 strokes, motor imagery task of Chinese characters writing with 10 strokes obtained stronger sensorimotor rhythm and better recognition performance ( < 0.05). This study indicated that, appropriately increasing the complexity of the motor imagery task of Chinese characters writing can obtain stronger motor imagery potential and improve the recognition accuracy of motor-imagery-based BCI, which provides a reference for the design of the motor-imagery-based BCI paradigm in the future.
基于运动想象的脑机接口（BCI）的传统范式较为抽象，无法有效引导用户调节大脑活动，从而限制了感觉运动皮层的激活程度。研究发现，汉字书写的运动想象任务更易被用户接受，并有助于引导他们调节自身的感觉运动节律。然而，不同汉字的书写复杂度（笔画数）不同，具有不同书写复杂度的汉字的运动想象任务对基于运动想象的BCI性能的影响仍不明确。本文共招募了12名健康受试者，用于研究具有两种不同书写复杂度（5画和10画）的汉字的运动想象任务对基于运动想象的BCI性能的影响。实验结果表明，与5画的汉字相比，书写10画汉字的运动想象任务获得了更强的感觉运动节律和更好的识别性能（<0.05）。本研究表明，适当增加汉字书写运动想象任务的复杂度可以获得更强的运动想象电位，并提高基于运动想象的BCI的识别准确率，这为未来基于运动想象的BCI范式设计提供了参考。
