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ASMI-BCI特征调制及分类性能研究
引用本文:边 琰,赵 丽,孙 永. ASMI-BCI特征调制及分类性能研究[J]. 电子测量与仪器学报, 2022, 36(3): 224-230
作者姓名:边 琰  赵 丽  孙 永
作者单位:天津职业技术师范大学天津市信息传感与智能控制重点实验室 天津 300222
基金项目:天津市应用基础与前沿技术研究计划项目(18JCYBJC88200)资助;
摘    要:基于运动想象(MI)的脑-机接口(BCI)近年来被应用于肢体运动功能的可塑性康复。采用视觉辅助刺激可以有效增强MI-BCI系统的分类性能,但视觉障碍患者无法使用。因此本文设计了基于听觉辅助刺激的ASMI-BCI,发现动态声音辅助刺激可以提高大脑运动相关皮层的兴奋性,增强系统的可分性特征。10名在校大学生(5男5女,平均22.6岁)3类实验范式(C-SW、C-DA、C-DV)的平均结果表明,C-SW范式分类正确率最低、C-DA次之、C-DV范式正确率最高。听觉辅助刺激范式的最优分类正确率可达76.03%,相比传统MI-BCI范式显著性提升了8.83%,且60%的被试使用该范式的分类正确率可高于70%。使用动态听觉辅助刺激范式可以为视觉障碍患者提供一种特征调制和BCI性能增强的新模式、新方法。

关 键 词:脑-机接口  运动想象  听觉辅助刺激  特征调制  分类性能

Research on feature modulation and classification performance of ASMI-BCI
Bian Yan,Zhao Li,Sun Yong. Research on feature modulation and classification performance of ASMI-BCI[J]. Journal of Electronic Measurement and Instrument, 2022, 36(3): 224-230
Authors:Bian Yan  Zhao Li  Sun Yong
Affiliation:1.Tianjin Information Sensing & Intelligent Control Key Lab, Tianjin University of Technology and Education
Abstract:Brain-computer interface (BCI) based on motor imagery (MI) has been applied to the plasticity rehabilitation of limb motorfunction in recent years. Visual assistant stimulus can improve the classification performance of MI-BCI. However, for users withimpaired visual system, visual assistant stimulus cannot be used. Therefore, this paper designs ASMI-BCI based on auditory assistantstimulus. It has been found that dynamic acoustic assistant stimulus could improve the excitability of motor related cortex, and enhancedthe separability features of related frequency bands. The average classification results of the three experimental paradigms (C-SW, CDA, C-DV ) for 10 college students (5 males and 5 females, with an average age of 22. 6 years old) showed that the classificationaccuracy of C-SW paradigm was the lowest, followed by C-DA, and the accuracy of C-DV paradigm was the highest. The optimalclassification accuracy of the auditory assistant stimulus paradigm was 76. 03% and the average classification accuracy was significantlyimproved by 8. 83% compared with the traditional MI-BCI paradigm. For 60% of the subjects, the classification accuracy of thisparadigm can reach higher than 70%. The dynamic auditory assistant stimulus paradigm can provide a new pattern and method of featuremodulation and BCI performance enhancement for patients with visual impairment.
Keywords:brain-computer interface ( BCI )   motor imagery ( MI )   auditory assistant stimulus   feature modulation  classification performance
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