基于脑机接口技术的写字系统建模仿真与实现

doi:10.16182/j.issn1004731x.joss.201812001

系统仿真学报 ›› 2018, Vol. 30 ›› Issue (12): 4499-4505.doi: 10.16182/j.issn1004731x.joss.201812001

• 专栏:生机电一体化系统建模与仿真 • 下一篇

基于脑机接口技术的写字系统建模仿真与实现

陈超^1,2, 平尧¹, 郝斌^3,*, 徐瑞²

1.天津理工大学电气电子工程学院,天津 300384;
2.天津大学医学工程与转化医学研究院,天津 300072;
3.天津理工大学中环信息学院,天津 300380

收稿日期:2010-10-18 修回日期:2010-10-30 出版日期:2018-12-10 发布日期:2019-01-03
通讯作者: 郝斌(1985-),男,山东,硕士,实验师,研究方向为机械工程。
作者简介:陈超(1984-),男,福建,博士,副教授,研究方向为脑信息处理与智能机器人; 平尧（1994-）,男,湖北,硕士,研究方向为脑信息处理与智能机器人。
基金资助:
国家重点研发计划(2018YFC1314500), 国家自然科学基金(61806146)

Modeling, Simulation and Realization of Writing System Based on BCI Technology

Chen Chao^1,2, Ping Yao¹, Hao Bin^3,*, Xu Rui²

1.Tianjin University of Technology, Tianjin 300384, China;
2.Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China;
3.Tianjin University of Technology Central Institute of Information, Tianjin 300380, China

Received:2010-10-18 Revised:2010-10-30 Online:2018-12-10 Published:2019-01-03

摘要/Abstract

摘要： 针对生机电一体化系统中生物体与机电装置之间的信息传递与交互能力不足的问题,利用脑电采集设备Emotiv EPOC和机械臂,搭建了一个信息传输速率较快的基于脑机接口技术的写字系统并进行了系统建模仿真与实现。在系统建模中通过带通滤波和CCA(Canonical Correlation Analysis)算法组合对稳态视觉诱发电位进行频率识别,其四分类的准确率高达91.6%。在线实验中通过Emotiv EPOC控制机械臂实现了对简单汉字的书写,达到了系统建模仿真的目的。

关键词: 生机电一体化, 脑机接口, 稳态视觉诱发电位, Emotiv EPOC, 机械臂, 典型相关性分析

Abstract: In order to solve the problem of insufficient information transmission and interaction between organisms and electromechanical devices in the integrated system of vital electricity, Emotiv EPOC and mechanical arm of eeg acquisition equipment were used to build a writing system based on brain-computer interface technology with faster information transmission rate The system modeling and simulation were conducted. In the system modeling, the frequency identification of steady-state visual evoked potential was carried out by a combination of bandpass filtering and Canonical Correlation Analysis algorithm, and the accuracy rate of the four classifications was as high as 91.6%. In the online experiment, Emotiv EPOC controlled the mechanical arm to write simple Chinese characters, which showed the purpose of system modeling and simulation was achieved.

Key words: electromechanical integration, brain-computer interface, steady-state visual evoked potential, Emotiv EPOC, mechanical arm, typical correlation analysis

中图分类号:

TP391.9

陈超, 平尧, 郝斌, 徐瑞. 基于脑机接口技术的写字系统建模仿真与实现[J]. 系统仿真学报, 2018, 30(12): 4499-4505.

Chen Chao, Ping Yao, Hao Bin, Xu Rui. Modeling, Simulation and Realization of Writing System Based on BCI Technology[J]. Journal of System Simulation, 2018, 30(12): 4499-4505.

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基于脑机接口技术的写字系统建模仿真与实现

Modeling, Simulation and Realization of Writing System Based on BCI Technology

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