SIA OpenIR  > 机器人学研究室
NIRS-based classification of clench force and speed motor imagery with the use of empirical mode decomposition for BCI
Yin XX(尹旭贤); Xu BL(徐保磊); Jiang ZH(蒋长好); Fu YF(伏云发); Wang ZD(王志东); Li HY(李洪谊); Shi G(石刚)
作者部门机器人学研究室
关键词Brain-computer Interface(Bci) Near-infrared Spectroscopy(Nirs) Empirical Mode Decomposition(Emd) Joint Mutual Information(Jmi)
发表期刊Medical Engineering and Physics
ISSN1350-4533
2015
卷号37期号:3页码:280-286
收录类别SCI ; EI
EI收录号20150600487252
WOS记录号WOS:000352249800004
产权排序1
摘要Near-infrared spectroscopy (NIRS) is a non-invasive optical technique used for brain-computer interface (BCI). This study aims to investigate the brain hemodynamic responses of clench force and speed motor imagery and extract task-relevant features to obtain better classification performance. Given the non-stationary characteristics of real hemodynamic measurements, empirical mode decomposition (EMD) was applied to reduce the physiological noise overwhelmed in the task-relevant NIRS signals. Compared with continuous wavelet decomposition, EMD does not require a pre-determined basis function. EMD decomposes the original signals into a set of intrinsic mode functions (IMFs). In this study, joint mutual information was applied to select the optimal features, and support vector machine was used as a classifier. Offline and pseudo-online analyses showed that the most feasible classification accuracy can be obtained using IMFs as input features. Accordingly, an alternative feature is provided to develop the NIRS-BCI system. © 2015 IPEM.
语种英语
引用统计
被引频次:9[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/15747
专题机器人学研究室
通讯作者Yin XX(尹旭贤)
作者单位1.State Key Laboratory of Robotics, Shenyang Institute of Automation (SIA), Chinese Academy of Sciences (CAS), Shenyang 110016, China
2.University of Chinese Academy of Sciences, Beijing 100049, China
3.Key Laboratory of Motor and Brain imaging, Capital Institute of Physical Education, Beijing, 100088, China
4.School of Automation and Information Engineering, Kunming University of Science and Technology, Kunming, 650500, China
5.Department of Advanced Robotics, Chiba Institute of Technology, Chiba, 2750016, Japan
6.School of Mechanical Engineering and Automation, Northeastern University, Shenyang, China
推荐引用方式
GB/T 7714
Yin XX,Xu BL,Jiang ZH,et al. NIRS-based classification of clench force and speed motor imagery with the use of empirical mode decomposition for BCI[J]. Medical Engineering and Physics,2015,37(3):280-286.
APA Yin XX.,Xu BL.,Jiang ZH.,Fu YF.,Wang ZD.,...&Shi G.(2015).NIRS-based classification of clench force and speed motor imagery with the use of empirical mode decomposition for BCI.Medical Engineering and Physics,37(3),280-286.
MLA Yin XX,et al."NIRS-based classification of clench force and speed motor imagery with the use of empirical mode decomposition for BCI".Medical Engineering and Physics 37.3(2015):280-286.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
NIRS-based classific(1679KB)期刊论文出版稿开放获取ODC PDDL浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Yin XX(尹旭贤)]的文章
[Xu BL(徐保磊)]的文章
[Jiang ZH(蒋长好)]的文章
百度学术
百度学术中相似的文章
[Yin XX(尹旭贤)]的文章
[Xu BL(徐保磊)]的文章
[Jiang ZH(蒋长好)]的文章
必应学术
必应学术中相似的文章
[Yin XX(尹旭贤)]的文章
[Xu BL(徐保磊)]的文章
[Jiang ZH(蒋长好)]的文章
相关权益政策
暂无数据
收藏/分享
文件名: NIRS-based classification of clench force and speed motor imagery with the use of empirical mode decomposition for BCI.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。