基于脑电和眼电的运动想象多尺度识别方法研究

doi:10.3969/j.issn.0372-2112.2018.03.029

电子学报 ›› 2018, Vol. 46 ›› Issue (3): 714-720.DOI: 10.3969/j.issn.0372-2112.2018.03.029

基于脑电和眼电的运动想象多尺度识别方法研究

孙曜^1,2, 文成林², 韦巍¹

1. 浙江大学电气工程学院, 浙江杭州 310018;
2. 杭州电子科技大学自动化学院, 浙江杭州 310058

收稿日期:2016-12-13 修回日期:2017-01-24 出版日期:2018-03-25
- 作者简介:
- 孙曜,女,1975年生,安徽马鞍山人.浙江大学控制理论与控制工程专业博士研究生.主要研究方向为模式识别、生物医学信号处理.E-mail:sunyao@hdu.edu.cn;文成林,男,1963年生,河南开封人.1999年西北工业大学控制理论与控制工程专业毕业,获工学博士学位;2002年清华大学控制科学与工程博士后流动站出站.现为杭州电子科技大学教授,博士生导师,系统科学与控制工程研究所所长,中国电子学会高级会员,中国自动化学会过程故障诊断与技术专委会委员、中国自动化学会智能控制专委会委员,主要从事多源信息融合与目标检测识别和跟踪,复杂系统故障诊断与健康管理等领域的研究工作.E-mail:wencl@hdu.edu.cn;韦巍,男,1964年生,浙江东阳人.1994年浙江大学电气工程学院毕业,获工学博士学位.现为浙江大学教授、博士生导师,电气工程学院院长,中国电工技术学会理事、中国人工智能学会理事、IEEE Intelligent Systems Applications TC专委会委员,主要从事电气自动化、模式识别、智能系统与智能控制等方面的研究工作.E-mail:wwei@zju.edu.cn
- 基金资助:
- 国家自然科学基金 (No.61503123，No.61304186）

Research on EEG and EOG Based Multiscale Recognization Method of Motor Imagery

SUN Yao^1,2, WEN Cheng-lin², WEI Wei¹

1. College of Electrical Engineering, Zhejiang University, Hangzhou, Zhejiang 310018, China;
2. School of Automation, Hangzhou Dianzi University, Hangzhou, Zhejiang 310058, China

Received:2016-12-13 Revised:2017-01-24 Online:2018-03-25 Published:2018-03-25

摘要/Abstract

摘要： 基于脑电信号对同一肢体不同动作想象模式进行识别的正确率低，已成为基于脑机接口对肢体瘫痪患者进行运动想象训练监控的方法，获得临床应用前必须解决的瓶颈问题.针对该问题，本文提出一种利用运动想象时眼睛的活动状态与所想象肢体动作之间存在的耦合关系，进行运动想象多尺度识别的新方法.该方法首先在大尺度上，利用脑电信号对运动想象是否发生进行识别，再结合同一运动想象过程眼电信号协同变化模式的识别结果，基于决策融合在更精细的尺度上，对同一肢体不同动作的想象模式进行识别.实验结果表明，仅基于脑电进行右臂三种动作想象模式识别的平均正确率为63.0%，而应用所提出方法可以将其提高到91.4%.所提出方法可望有临床应用前景.

关键词: 脑电, 眼电, 运动想象模式识别, 监控

Abstract: The accuracy on electroencephalogram (EEG) based motor imagery recognization of different movements of a same limb is low. It constrains the monitor method, which monitor motor imagery training of patients with limb paralysis based on brain computer interface, to be used in clinical. Aiming at the problem, in this paper a new method of multiscale recognization of motor imagery is proposed. It is based on the coupling relationship between eye movement and imagined movement during motor imagery. In this method, first of all EEG is applied to judge whether motor imagery occurs on a large scale, and then combined with the recognization result of electrooculogram (EOG), which changes cooperatively with EEG during the same motor imagery period, the different movements of a same limb is recognized using decision fusion on a finer scale. The results of experiments reveal that the average recognization accuracy of three kinds of movement imagery of the right arm can be promoted from 63. 0% (only with EEG) to 91. 4% (with the proposed method). The proposed method may be applied in clinical in the future.

Key words: electroencephalogram, electrooculogram, recognization of motor imagery, monitor

中图分类号:

TP391

孙曜, 文成林, 韦巍. 基于脑电和眼电的运动想象多尺度识别方法研究[J]. 电子学报, 2018, 46(3): 714-720.

SUN Yao, WEN Cheng-lin, WEI Wei. Research on EEG and EOG Based Multiscale Recognization Method of Motor Imagery[J]. Acta Electronica Sinica, 2018, 46(3): 714-720.

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基于脑电和眼电的运动想象多尺度识别方法研究

Research on EEG and EOG Based Multiscale Recognization Method of Motor Imagery

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