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题名:
NIRS-based classification of clench force and speed motor imagery with the use of empirical mode decomposition for BCI
作者: 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
通讯作者: 尹旭贤
关键词: Brain-computer interface(BCI) ; Near-infrared spectroscopy(NIRS) ; Empirical mode decomposition(EMD) ; Joint mutual information(JMI)
刊名: Medical Engineering and Physics
ISSN号: 1350-4533
出版日期: 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
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/15747
Appears in Collections:机器人学研究室_期刊论文

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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

Recommended Citation:
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.
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