一种基于脑电信号的眼动方向分类方法  

Approach to Classification of Eye Movement Directions Based on EEG Signal

作　　者：程时伟[1] 陈一健 徐静如 张柳新 吴剑锋 孙凌云[4] CHENG Shi-wei;CHEN Yi-jian;XU Jing-ru;ZHANG Liu-xin;WU Jian-feng;SUN Ling-yun(School of Computer Science and Technology,Zhejiang University of Technology,Hangzhou 310023,China;Lenovo Research,Beijing 100085,China;Institute of Industrial Design,Zhejiang University of Technology,Hangzhou 310023,China;State Key Lab of CAD&CG,Zhejiang University,Hangzhou 310027,China)

机构地区：[1]浙江工业大学计算机科学与技术学院,杭州310023 [2]联想研究院,北京100085 [3]浙江工业大学工业设计研究院,杭州310023 [4]浙江大学CAD&CG国家重点实验室,杭州310027

出　　处：《计算机科学》2020年第4期112-118,共7页Computer Science

基　　金：国家重点研发计划课题(2016YFB1001403);国家自然科学基金(61772468,61672451)。

摘　　要：为了提高基于眼电的眼动方向的识别准确性,文中利用包含眼电伪迹的脑电信号,提出了一种新的眼动方向分类方法。首先,在10-20国际标准导联配置下,通过脑电仪采集靠近人脑额叶处的AF7,F7,FT7,T7,AF8,F8,FT8,T8这8个通道的脑电信号;然后,通过基线移除、归一化、最小二乘法降噪等进行数据预处理;最后,采用支持向量机的方法进行眼动方向的多次二分类,并使用投票策略实现眼动方向的四分类识别。实验结果表明,所提方法进行眼动方向分类时,在上、下、左、右4个方向上的分类率分别达到了78.47%,72.22%,84.03%,79.86%,平均分类率达到了78.65%。与已有的分类方法相比,所提方法的分类准确率更高,分类算法的实现过程更简单,这进一步验证了利用脑电信号识别眼动方向的可行性和有效性。In order to improve the accuracy of eye movement directions identification based on electro-oculogram(EOG)signals,this paper utilized the electrooculogram(EEG)signals containing EOG artifacts and proposed a new approach to classify eye movement directions.Firstly,EEG signals from the 8 channels in the frontal lobe of the human brain are collected,and EEG data pre-processing is made,including data normalization and least squares based denoising.Then support vector machine based method is applied to perform multiple binary-classification,and finally voting strategy is used to solve four-classification problems,thus achieving eye movement directions identification.The experiment results show when using the approach of this paper to classify eye movement directions,the classification accuracy rates in the upper,lower,left and right directions are 78.47%,72.22%,84.03%,79.86%respectively,and the average classification accuracy rates reach 78.65%.In addition,compared with the existed classification methods,the classification accuracy rate of this paper is higher,and the classification algorithm is simpler.It is validated the feasibility and effectiveness of using EEG signals to identify eye movement directions.

关 键 词：脑机接口 脑电 眼动跟踪 眼电 人机交互 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]