基于可穿戴式脑磁图的视觉混合脑机接口研究  

Study of Visual Hybrid Brain-Computer Interface Based on Wearable Magnetoencephalogram

作　　者：王晨旭 郭旭 王慧[2,3] 张欣 常严[2,3] 郭清乾 胡涛[2,3] 冯晓宇 杨晓冬 WANG Chenxu;GUO Xu;WANG Hui;ZHANG Xin;CHANG Yan;GUO Qingqian;HU Tao;FENG Xiaoyu;YANG Xiaodong(School of Medical Imaging,Xuzhou Medical University,Xuzhou 221004,China;Suzhou Institute of Biomedical Engineering and Technology,Chinese Academy of Sciences,Suzhou 215163,China;Jihua Laboratory,Foshan 528000,China)

机构地区：[1]徐州医科大学医学影像学院,江苏徐州221004 [2]中国科学院苏州生物医学工程技术研究所,江苏苏州215163 [3]季华实验室,广东佛山528200

出　　处：《波谱学杂志》2024年第4期405-417,共13页Chinese Journal of Magnetic Resonance

基　　金：季华实验室项目--新一代可穿戴脑磁图仪研制(X190131TD190).

摘　　要：新兴的可穿戴式脑磁图技术为脑机接口(BCI)提供高质量数据奠定了基础.为探究可穿戴式脑磁图应用于视觉混合BCI上的可行性,本文基于稳态视觉诱发场(SSVEF)和Alpha波设计了SSVEF-Alpha混合BCI,并在不同分类模型上进行了性能对比结果表明,基于用户依赖(UD)的训练方法,混合BCI6分类平均分类准确率为(93.29±1.69)%,信息传输速率可达86.81bits/min,且使用短数据长度进行用户独立(UI)的训练方法比免训练的方法更具优越性.本研究验证了视觉混合BCI的有效性,为进一步开发设计可穿戴式脑磁图的BCI应用产品提供参考范例.The emerging wearable magnetoencephalography technology lays the foundation for brain-computer interface to provide high-quality data.To explore the feasibility of applying wearable magnetoencephalography in visual hybrid brain-computer interface,a SSVEF-Alpha hybrid brain-computer interface is designed based on steady-state visual evoked field and Alpha wave,and the performance is compared with different classification models.The results show that based on the user-dependent training method,the average classification accuracy of hybrid brain-computer interface is(93.29±1.69)%,the information transmission rate can reach 86.81 bits/min.And the user-independent training method with short data length shows superiority over the training-free method.This study verifies the effectiveness of visual hybrid brain-computer interface and provides a reference example for further development and design of brain-computer interface products of wearable magnetoencephalography.

关 键 词：脑机接口 可穿戴脑磁图 稳态视觉诱发场 Alpha波 分类准确率 信息传输速率 

分 类 号：O441.5[理学—电磁学] Q64[理学—物理]