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Classification of Hemodynamic Responses Associated With Force and Speed Imagery for a Brain-Computer Interface
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)
Department机器人学研究室
Source PublicationJOURNAL OF MEDICAL SYSTEMS
ISSN0148-5598
2015
Volume39Issue:5Pages:1-8
Indexed BySCI
WOS IDWOS:000352821900012
Contribution Rank1
Funding OrganizationNational Natural Science Foundation (NNSF) of China [61203368, 81470084, 61463024] ; General Reserve Department of PLA [9140A26060214ZK63424]
KeywordFunctional Near-infrared Spectroscopy (Fnirs) Brain-computer Interface (Bci) Joint Mutual Information (Jmi) Extreme Learning Machine (Elm) Force/speed Imagery
AbstractFunctional near-infrared spectroscopy (fNIRS) is an emerging optical technique, which can assess brain activities associated with tasks. In this study, six participants were asked to perform three imageries of hand clenching associated with force and speed, respectively. Joint mutual information (JMI) criterion was used to extract the optimal features of hemodynamic responses. And extreme learning machine (ELM) was employed to be the classifier. ELM solved the major bottleneck of feedforward neural networks in learning speed, this classifier was easily implemented and less sensitive to specified parameters. The 2-class fNIRS-BCI system was firstly built with an average accuracy of 76.7%, when all force and speed tasks were categorized as one class, respectively. The multi-class systems based on different levels of force and speed attempted to be investigated, the accuracies were moderate. This study provided a novel paradigm for establishing fNIRS-BCI system, and provided a possibility to produce more degrees of freedom in BCI system.
Language英语
Citation statistics
Cited Times:14[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/16225
Collection机器人学研究室
Corresponding AuthorXu BL(徐保磊)
Affiliation1.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.Department of Advanced Robotics, Chiba Institute of Technology, Chiba 2750016, Japan
5.School of Mechanical Engineering & Automation, Northeastern University, Shenyang, China
6.School of Automation and Information Engineering, Kunming University of Science and Technology, Kunming 650500, China
Recommended Citation
GB/T 7714
Yin XX,Xu BL,Jiang ZH,et al. Classification of Hemodynamic Responses Associated With Force and Speed Imagery for a Brain-Computer Interface[J]. JOURNAL OF MEDICAL SYSTEMS,2015,39(5):1-8.
APA Yin XX.,Xu BL.,Jiang ZH.,Fu YF.,Wang ZD.,...&Shi G.(2015).Classification of Hemodynamic Responses Associated With Force and Speed Imagery for a Brain-Computer Interface.JOURNAL OF MEDICAL SYSTEMS,39(5),1-8.
MLA Yin XX,et al."Classification of Hemodynamic Responses Associated With Force and Speed Imagery for a Brain-Computer Interface".JOURNAL OF MEDICAL SYSTEMS 39.5(2015):1-8.
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