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An inter-subject model to reduce the calibration time for motion imagination-based brain-computer interface
Zou YJ(邹宜君)1; Zhao XG(赵新刚)2; Chu YQ(褚亚奇)1,2; Zhao YW(赵忆文)2; Xu WL(徐卫良)3; Han JD(韩建达)2
Department机器人学研究室
Source PublicationMedical and Biological Engineering and Computing
ISSN0140-0118
2019
Volume57Issue:4Pages:939-952
Indexed BySCI ; EI
EI Accession number20184906213055
WOS IDWOS:000463717500015
Contribution Rank1
Funding OrganizationNational High Technology Research and Development Program of China (863 Program) ; National Natural Science Foundation of China
KeywordBrain-computer interface (BCI) Electroencephalogram (EEG) Machine learning Movement imagination Common spatial pattern Inter-subject model
AbstractA major factor blocking the practical application of brain-computer interfaces (BCI) is the long calibration time. To obtain enough training trials, participants must spend a long time in the calibration stage. In this paper, we propose a new framework to reduce the calibration time through knowledge transferred from the electroencephalogram (EEG) of other subjects. We trained the motor recognition model for the target subject using both the target’s EEG signal and the EEG signals of other subjects. To reduce the individual variation of different datasets, we proposed two data mapping methods. These two methods separately diminished the variation caused by dissimilarities in the brain activation region and the strength of the brain activation in different subjects. After these data mapping stages, we adopted an ensemble method to aggregate the EEG signals from all subjects into a final model. We compared our method with other methods that reduce the calibration time. The results showed that our method achieves a satisfactory recognition accuracy using very few training trials (32 samples). Compared with existing methods using few training trials, our method achieved much greater accuracy. [Figure not available: see fulltext.
Language英语
WOS SubjectComputer Science, Interdisciplinary Applications ; Engineering, Biomedical ; Mathematical & Computational Biology ; Medical Informatics
WOS KeywordCOMMON SPATIAL-PATTERN
WOS Research AreaComputer Science ; Engineering ; Mathematical & Computational Biology ; Medical Informatics
Funding ProjectNational High Technology Research and Development Program of China (863 Program)[2015AA042301] ; National Natural Science Foundation of China[61773369] ; National Natural Science Foundation of China[61573340] ; National Natural Science Foundation of China[61503374]
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Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/23678
Collection机器人学研究室
Corresponding AuthorZhao XG(赵新刚)
Affiliation1.University of Chinese Academy of Sciences, Beijing 100049, China
2.Key Laboratory of Networked Control System, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
3.Department of Mechanical Engineering, University of Auckland, Auckland, New Zealand
Recommended Citation
GB/T 7714
Zou YJ,Zhao XG,Chu YQ,et al. An inter-subject model to reduce the calibration time for motion imagination-based brain-computer interface[J]. Medical and Biological Engineering and Computing,2019,57(4):939-952.
APA Zou YJ,Zhao XG,Chu YQ,Zhao YW,Xu WL,&Han JD.(2019).An inter-subject model to reduce the calibration time for motion imagination-based brain-computer interface.Medical and Biological Engineering and Computing,57(4),939-952.
MLA Zou YJ,et al."An inter-subject model to reduce the calibration time for motion imagination-based brain-computer interface".Medical and Biological Engineering and Computing 57.4(2019):939-952.
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