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基于视觉意象法的认知脑机接口的开发

Development of a Cognitive Brain-Machine Interface Based on a Visual Imagery Method.

作者信息

Koizumi Koji, Ueda Kazutaka, Nakao Masayuki

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul;2018:1062-1065. doi: 10.1109/EMBC.2018.8512520.

Abstract

In the field of brain-machine interface (BMI) research, the development of cognitive BMI is a hot topic because it may lead to more intuitive and goal-directed findings than existing BMI technology. In this study, we devised a "visual-imagery method," which enables visual imaging of the operation of a target. We also investigated an "inner-speech method," which comprised internal pronunciation of words without emitting sounds, and an "inner-speech + visual-imagery method," which combined the two methods. When only the high $\gamma$ band (60-120 Hz) power in the prefrontal cortex was used, the average accuracy of the 15 participants, with 20-fold crossvalidation, was 81.3% in inner speech, 84.6% in visual imagery, and 83.2% in inner speech + visual imagery. This study also found that the frontal pole was the most useful region in the prefrontal cortex.

摘要

在脑机接口(BMI)研究领域,认知BMI的发展是一个热门话题,因为它可能比现有的BMI技术带来更直观、更具目标导向性的研究成果。在本研究中,我们设计了一种“视觉意象法”,它能够对目标操作进行视觉成像。我们还研究了一种“内心言语法”,即不出声地在内心默念单词,以及一种将这两种方法结合起来的“内心言语 + 视觉意象法”。当仅使用前额叶皮层中的高γ波段(60 - 120赫兹)功率时,15名参与者在20折交叉验证下的平均准确率分别为:内心言语法81.3%、视觉意象法84.6%、内心言语 + 视觉意象法83.2%。本研究还发现,额极是前额叶皮层中最有用的区域。

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