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

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.