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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
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
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
WOS记录号: WOS:000352249800004
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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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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