Suppr超能文献

[脑机接口中手臂运动想象时人类脑电图模式的侧化]

[Lateralization of EEG Patterns in Humans during Motor Imagery of Arm Movements in the Brain-Computer Interface].

作者信息

Vasilyev A N, Liburkina S P, Kaplan A Ya

出版信息

Zh Vyssh Nerv Deiat Im I P Pavlova. 2016 May;66(3):302-312.

Abstract

In this study EEG patterns ofsensorimotor rhythm were examined in 10 healthy subjects while perform- ing motor imagery of upper arm and hand movements. Participants received visual feedback through so called brain-computer interface (BCI) used for detection of user-specific spatio-temporal.EEG patterns associated with performed mental tasks. During the course study,.all of the subjects were able to modulate their sensorimotor EEG by performing motor imagery of shoulder and fingers movements. Patterns during imagery of shoulder movements were found to have more pronounced contralateral localization, than those during hand movements' imagery. That led to significantly better classification accuracies of the most lateralized patterns when discriminating between left and right hand (72 and 58% corresponding to shoulder and hand motor imagery). Value of difference of patterns' lateralization indexes had shown strong correlation with classification accuracy, suggests it could be used as a good ref- erence mark for.choosing optimal motor imagery tasks for BCI application.

摘要

在本研究中,对10名健康受试者在进行上臂和手部运动的运动想象时的感觉运动节律脑电图模式进行了检查。参与者通过所谓的脑机接口(BCI)获得视觉反馈,该接口用于检测与执行的心理任务相关的用户特定时空脑电图模式。在研究过程中,所有受试者都能够通过进行肩部和手指运动的运动想象来调节他们的感觉运动脑电图。发现肩部运动想象期间的模式比手部运动想象期间的模式具有更明显的对侧定位。这导致在区分左手和右手时,最具偏侧化模式的分类准确率显著提高(分别对应肩部和手部运动想象的准确率为72%和58%)。模式偏侧化指数的差异值与分类准确率显示出强相关性,表明它可作为为脑机接口应用选择最佳运动想象任务的良好参考标志。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验